DEV Community: Matt Kundo

Meta Adaptive Ranking Model: What Instagram Advertisers Gain in 2026 | MKDM

Matt Kundo — Fri, 03 Apr 2026 14:18:36 +0000

Home / Blog / Meta Adaptive Ranking Model Recent News & Paid Media Apr 03, 2026 7 min read Meta Adaptive Ranking Model: What Instagram Advertisers Gain in 2026

Meta launched an Adaptive Ranking Model for Instagram ads that boosts conversions by 3% and CTR by 5%. Here is what it means for your campaigns and how to take advantage.

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Meta's Adaptive Ranking Model Gives Instagram Ads a Measurable Boost in 2026

A 3% increase in conversions and a 5% jump in click-through rates. Those are the numbers Meta's engineering team published about its Adaptive Ranking Model for Instagram ads, and they represent one of the most significant backend upgrades to the Meta adaptive ranking model Instagram ads 2026 platform has seen in recent memory. For advertisers spending real money on Instagram, this is not a press release to skim past. It is a structural change to how the platform decides which ads reach which people, and it directly affects your return on ad spend.

What Happened with Meta's Ad Serving Infrastructure

Meta rolled out its Adaptive Ranking Model for Instagram during Q4 2025, with confirmed performance results arriving in early April 2026. The update replaces the platform's previous one-size-fits-all ad inference system with intelligent request routing that adjusts model complexity based on real-time user context and intent signals.

According to Marketing Dive's coverage, the new system processes more engagement elements in real time while actually using less computing power. That is a notable engineering achievement: better results with lower overhead. The model uses LLM-scale intelligence to evaluate user readiness signals, such as whether someone is casually browsing or actively comparing products, then allocates compute resources accordingly.

The technical infrastructure behind it includes multi-card GPU architectures capable of scaling to over one trillion parameters while maintaining sub-second latency, as detailed in Meta's engineering blog post. For advertisers, the takeaway is simple: Instagram now does a better job of showing your ads to people who are likely to act on them.

Why This Matters for Your Marketing

Better Targeting Without Higher Spend

The most immediate impact is improved efficiency. When the ad platform gets smarter about matching ads to users, your existing budget works harder. A 3% conversion lift might sound modest, but applied across a monthly ad budget of even $5,000 to $10,000, that translates to meaningful additional revenue without touching your spend.

This aligns with what eMarketer's analysis confirms: Meta is pushing toward full ad automation, and the Adaptive Ranking Model is the engine driving that shift. The platform is getting better at finding your customers for you.

What This Means for Small Business Instagram Ad Targeting Improvements

Small businesses often lack the data volume that large brands use to train algorithms. The Adaptive Ranking Model changes that equation. By processing richer real-time signals instead of relying solely on historical audience data, the system can identify high-intent users even for smaller accounts with limited pixel history. This narrows the performance gap between big-budget and small-budget advertisers.

The Broader AI Ad Automation Trend

This update fits into a larger pattern. eMarketer projects AI-powered ad spend will reach $57 billion in 2026, a 63% jump from prior levels. Meta and Google are both accelerating their AI-driven ad tools, with Advantage+ and Performance Max leading the charge. The brands seeing the best results are the ones feeding these systems clean data and strong creative rather than fighting the automation.

Action Plan: 8 Steps to Capitalize on the Meta Advantage+ Ad Updates

Audit your conversion tracking setup. The Adaptive Ranking Model optimizes for conversions. If your Meta Pixel and Conversions API are not properly configured, the model cannot do its job. Verify that key conversion events (purchases, leads, sign-ups) fire correctly.
Review your campaign structure for Advantage+ compatibility. Campaigns using Advantage+ give the new model more room to optimize. If you are still running heavily segmented manual campaigns, test consolidating into Advantage+ Shopping or Advantage+ App campaigns.
Expand your creative library. A smarter algorithm means creative quality matters more than ever. The model can now match specific creative styles to specific user preferences in real time. Give it more options to work with by testing diverse ad formats, copy angles, and visual styles.
Test broader audience targeting. With improved ranking, narrow audience segments may actually limit performance. Experiment with broader targeting and let the algorithm find your customers. Start with a 10% budget allocation and compare results over 14 days.
Review your bidding strategy. Efficiency gains from the new model may allow more aggressive cost-per-action targets. Consider switching from cost cap to bid cap on your top-performing campaigns to test whether the improved ranking delivers at lower thresholds.
Monitor CPM and CPC trends over the next 30 days. Establish a performance baseline now so you can measure the impact as the model continues to learn from your campaign data.
Compare Q1 2026 vs. Q4 2025 Instagram ad performance. Pull your metrics side by side. The Adaptive Ranking Model launched in Q4 2025, so Q1 2026 data should already reflect early improvements.
Consider increasing Instagram ad budget if early results are positive. When efficiency improves, scaling spend becomes more attractive. If your cost per acquisition drops, reinvest the savings into higher volume.

How I Can Help You Navigate This

I manage Meta ad campaigns for businesses that want to get ahead of platform changes instead of reacting to them. The Adaptive Ranking Model rewards advertisers who feed the system properly: clean conversion data, diverse creative, and smart campaign structure. That is exactly what I build for my clients.

If you are running Instagram ads and want to make sure your campaigns are positioned to benefit from this update, or if you have been thinking about launching paid social for the first time, I would be happy to take a look at your setup. Get in touch here and we can talk through your situation.

You can also read more about how I approach Meta advertising management to see if it is a good fit.

Frequently Asked Questions

What is Meta's Adaptive Ranking Model and how does it affect my Instagram ads?

Meta's Adaptive Ranking Model is an upgraded ad serving system that uses LLM-scale AI to match ads to users based on real-time engagement signals. It replaces the previous one-size-fits-all approach with intelligent request routing, delivering a 3% increase in conversions and 5% increase in click-through rates for Instagram advertisers. The model evaluates whether a user is browsing casually or ready to convert, then adjusts which ads it shows accordingly.

Do I need to change my Instagram ad settings to benefit from this update?

No manual changes are required for the basic improvements. The Adaptive Ranking Model works on the backend, automatically improving how Instagram delivers your ads to the right users. That said, you can maximize the benefit by ensuring your conversion tracking is properly configured, expanding your creative library with varied formats and messaging, and testing broader audience targeting through Advantage+ campaigns.

How much can I expect my Instagram ad performance to improve?

Meta reports an average 3% lift in conversions and 5% improvement in click-through rates across Instagram campaigns. Individual results vary based on your industry, creative quality, audience size, and conversion tracking setup. Advertisers with strong creative libraries and clean conversion data tend to see the largest gains. The best way to measure your specific impact is to compare your Q1 2026 metrics against your Q4 2025 baseline.

Is Meta's Adaptive Ranking Model related to Advantage+ campaigns?

Yes. The Adaptive Ranking Model powers the backend of Meta's Advantage+ suite. It is the AI engine that makes automated audience selection and creative optimization more effective. Running Advantage+ campaigns gives the model more flexibility to apply its improved targeting capabilities, which is why Meta recommends consolidating campaigns into Advantage+ formats when possible.

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View All Insights [ Marketing News & Paid Media 7 min read

Google Ads Experiments Auto-Apply: What Advertisers Must Know | MKDM

Matt Kundo — Fri, 03 Apr 2026 14:18:00 +0000

Home / Blog / Auto-Apply Experiments Recent News & Paid Media Apr 02, 2026 7 min read Google Ads Experiments Auto-Apply: What Advertisers Must Know

Google Ads quietly changed experiments to auto-apply winning variants by default. If you run A/B tests on your campaigns, this could push changes live without your review.

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Google Ads Experiments Auto-Apply: What Advertisers Must Know

Google Ads just flipped a default that most advertisers have not noticed yet. Experiments now auto-apply winning variants to your live campaigns once results hit a confidence threshold. No manual review. No approval step. The change, first reported by Search Engine Land after PPC specialist Bob Meijer flagged it, affects both directional results and statistical significance modes. If you are running A/B tests on your Google Ads campaigns right now, changes could be going live without you knowing about it.

What Happened with Google Ads Experiments Auto-Apply

Google Ads experiments have always let advertisers test campaign variations against a control. You would set up a test, split traffic, wait for results, then decide whether to apply the winner. That last step, the manual decision, is what changed.

The auto-apply setting is now enabled by default for new experiments. When your experiment reaches the configured confidence level, Google automatically pushes the winning variant into your live campaign. The platform offers two confidence modes: directional results (the default, lower threshold) and statistical significance at 80%, 85%, or 95% confidence levels, according to Search Engine Land's reporting.

There is one built-in safeguard: if your chosen success metric performs significantly worse in the test arm, the change will not auto-apply. But experiments only allow two success metrics. Everything else goes unmonitored. A third metric you care about, like cost per acquisition or return on ad spend, could quietly decline without triggering any protection. Google's official experiments documentation covers the mechanics, though details on the default change are limited.

Why This Matters for Your Marketing

PPC and Paid Media Teams

This is the most direct impact. Every active experiment in your Google Ads account could now auto-apply results without your sign-off. If you run tests across multiple campaigns or clients, the risk compounds. A winning variant that improves click-through rate but tanks conversion value could go live before anyone reviews the full picture. For agencies managing dozens of accounts, the operational risk is significant.

Budget and Financial Planning

Auto-applied changes can shift campaign behavior in ways that affect spend allocation. A test variant that wins on one metric might consume budget differently than expected. If your campaigns feed into broader financial forecasts, unreviewed changes introduce unpredictability. According to Improvado's analysis of Google Ads data challenges, discrepancies between Google Ads reporting and external analytics can already cause confusion. Auto-apply adds another layer of potential mismatch.

Marketing Strategy and Oversight

The broader pattern here matters as much as the specific change. Google continues to push automation as the default across its advertising platform. Smart bidding, broad match defaults, Performance Max's consolidated approach, and now auto-apply experiments all point in the same direction: less manual control, more algorithmic decision-making. Each individual change might be reasonable. Taken together, they systematically reduce the checkpoints where human judgment enters the process. Marketers who are not actively auditing their settings may find their campaigns operating under assumptions they never approved.

Action Plan: Protect Your Campaigns

Audit every active experiment right now. Open Google Ads, navigate to Experiments, and check the auto-apply setting on each one. Toggle it off for any experiment where you want manual control.
Set a standard operating procedure for new experiments. Before launching any future test, verify the auto-apply default and disable it if your workflow requires human review before applying changes.
Review your success metrics carefully. Since experiments only protect two metrics, make sure the two you select actually cover your most important KPIs. If you care about three or more metrics, manual review is essential.
Check experiments that already completed. If any experiments finished in the past few weeks, verify whether results were auto-applied. Look for the "Complete (Applied or Converted)" status on your Experiments page.
Document your experiment protocol. Write down your team's standard process: which confidence mode to use, when auto-apply is acceptable versus when manual review is required, and who is responsible for the final decision.
Monitor campaign performance post-experiment. Even after manually applying a winner, track performance for 7 to 14 days. Automated application skips this verification window entirely.
Consider confidence thresholds. If you do use auto-apply for low-risk tests, set the confidence to 95% statistical significance rather than accepting directional results. Higher thresholds reduce the chance of false positives.
Brief your clients or stakeholders. If you manage ads for others, proactively communicate this change. Transparency about platform defaults builds trust and prevents surprises.

How I Can Help

My Google Ads management approach involves manually reviewing every experiment before applying results to live campaigns. No auto-apply. No surprises. I track performance across all relevant metrics, not just the two Google lets you select as success criteria. If you are concerned about unreviewed changes affecting your ad spend, or if you want someone to audit your current experiment settings, reach out. I will review your account and make sure your testing process has the oversight it needs. You can also explore my full range of digital marketing services to see how I approach paid media management.

Frequently Asked Questions

What changed with Google Ads experiments auto-apply?

Google Ads now enables auto-apply for experiment winners by default. When an experiment reaches the configured confidence threshold (using directional results or statistical significance at 80%, 85%, or 95%), the winning variant is automatically applied to your live campaign without requiring manual approval. Previously, advertisers had to review results and manually apply winners.

How do I turn off auto-apply for Google Ads experiments?

You can disable auto-apply from the experiment's Report page inside Google Ads. Navigate to Experiments, select your active experiment, open the Report tab, and toggle off the auto-apply setting. Audit this setting for every active and future experiment to ensure changes are not pushed live without your review.

What are the risks of Google Ads auto-applying experiment results?

The main risk is that experiments only track two success metrics. If a third metric you care about (such as cost per acquisition or return on ad spend) declines during the test, auto-apply will not catch it. The winning variant gets pushed live based only on the metrics you selected, potentially hurting overall campaign performance in ways you did not anticipate.

Does auto-apply work with all Google Ads experiment types?

Auto-apply currently works with supported experiment types in Google Ads, including Search and Performance Max campaigns. The feature applies to both directional results mode (the default) and statistical significance mode. Check Google's official documentation for the latest list of supported campaign types.

Should I use auto-apply for my Google Ads experiments?

For simple, low-risk tests with clear success metrics, auto-apply can save time. For complex campaigns with multiple KPIs, high budgets, or nuanced performance goals, manual review is strongly recommended. The safest approach is to run experiments to statistical significance, review the full data across all metrics, and then apply winners yourself.

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View All Insights [ Paid Media 12 min read

Sales Conversion Rates: 2026 Benchmarks and How to Improve

Read Article → ](https://mattkundodigitalmarketing.com/blog/sales-conversion-rates-benchmarks/) [ 14 min read

Google Shopping Management: Complete Guide to Product Feed Optimization and Campaign Strategy

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Google Loyalty Ads Hit AI Mode: What Marketers Should Do Now

Read Article → ](https://mattkundodigitalmarketing.com/blog/google-loyalty-program-ads-ai-mode/) [ Recent News & Paid Media & Google Ads 7 min read

Veo in Google Ads: How to Use AI Video for Better Campaigns

Read Article → ](https://mattkundodigitalmarketing.com/blog/veo-google-ads-ai-video-generation/) Trusted by marketing teams at

Originally published at mattkundodigitalmarketing.com

New York AI Ad Disclosure Law: What Marketers Must Prepare For | MKDM

Matt Kundo — Wed, 01 Apr 2026 14:08:23 +0000

Home / Blog / NY AI Ad Disclosure Law Recent News & AI in Marketing Apr 01, 2026 7 min read New York AI Ad Disclosure Law: What Marketers Must Prepare For

New York's AI Transparency in Advertising and Synthetic Performer Disclosure Law takes effect June 9, 2026. Here's what the law requires and how to prepare your ad workflows before the deadline.

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New York AI Transparency Advertising Law 2026: A New Compliance Deadline for Marketers

New York just became one of the first states to pass a law specifically targeting AI-generated content in advertising. The AI Transparency in Advertising and Synthetic Performer Disclosure Law takes effect on June 9, 2026, and it creates concrete disclosure requirements for any commercial ad that uses AI-generated visuals, copy, or synthetic performers. If you're running ads that touch New York audiences (and if you're advertising online, you almost certainly are), this is a deadline worth circling.

The timing is notable. According to the IAB's 2026 U.S. framework, over 80% of ad workflows now incorporate AI tools at some stage. Most marketers are already using AI. Most aren't disclosing it. That gap is exactly what this law addresses.

What Happened

New York's legislature passed the AI Transparency in Advertising and Synthetic Performer Disclosure Law, which Governor Hochul signed into law in early 2026. As Global Legal Post reported, the law specifically targets consumer-facing advertising in sectors where AI "digital doubles" and synthetic performers have become common, particularly fashion and beauty, though its scope extends to all commercial advertising.

The law defines two key categories. AI-generated content covers any ad material (images, video, text) created or substantially modified by artificial intelligence. Synthetic performers are AI-generated likenesses of real or fictional people used in commercial contexts. Both require clear disclosure to consumers.

This sits within a broader wave of state-level AI regulation. According to the AI Transparency Coalition's March 2026 legislative update, at least five states now have active AI advertising disclosure bills in play, with Texas's SB 1050 following a similar model. New York's law is among the first to actually reach the governor's desk and get signed.

Why This Matters for Your Marketing

Paid Media and Creative Production

If your team uses AI tools to generate ad images, edit product photos, create video content, or write ad copy, every one of those outputs now needs a compliance check before it runs in front of New York audiences. The law doesn't distinguish between fully AI-generated content and AI-assisted content. If AI played a substantial role, disclosure is required. That's a critical distinction: touching up a product image with AI background removal likely qualifies, not just generating an entire ad from a text prompt.

The practical impact: your creative brief process needs an AI disclosure step. The IAB recommends a four-question pre-launch checklist: Was AI used? In what capacity? Does it require disclosure under applicable law? Is the disclosure visible and clear? That's a reasonable starting framework. For most teams, this means adding a single sign-off step to the approval chain, not rebuilding the entire process.

Influencer and Talent Partnerships

The synthetic performer provisions hit particularly hard in influencer marketing. If you're using AI-generated versions of real influencers, digital doubles for talent who aren't physically present, or entirely synthetic brand ambassadors, all of those now require explicit disclosure. This isn't just about protecting consumers. As JD Supra's legal analysis notes, New York's broader AI push also addresses performer rights and consent, meaning the talent side has new protections too.

Federal Preemption Uncertainty

One complication worth tracking: the White House released its National Policy Framework for Artificial Intelligence on March 20, 2026. As Jones Day's analysis explains, the framework proposes federal preemption of state AI laws that impose "undue burdens," and establishes an AI Litigation Task Force to challenge state regulations on constitutional grounds. That creates a real question about the long-term durability of state-level requirements like New York's.

My take: comply now, because the June deadline is real and federal preemption (if it happens at all) will take years to litigate. You don't want to be the test case. And even if federal rules eventually override state laws, the compliance infrastructure you build now (audit trails, disclosure templates, documented processes) will serve you regardless of which regulatory body ends up in charge.

Action Plan: Preparing for the June 2026 Deadline

Audit your current ad workflows. Identify every point where AI tools generate or modify creative assets. Include image generators, copywriting tools, video editors, and voice synthesis.
Map your audience reach. Determine which campaigns serve ads to New York consumers. If you run national digital campaigns, assume New York is in scope.
Create a disclosure template. Develop clear, plain-language disclosure labels like "AI-generated image" or "This ad features a synthetic performer." The IAB framework recommends visible, contextual labels rather than buried fine print.
Update creative briefs. Add mandatory AI usage documentation to every brief. Track which tools were used, what they generated, and whether disclosure is required.
Build an audit trail. Maintain records of AI tool usage per campaign. If regulators ask, you need documentation showing what was AI-generated and how you disclosed it.
Review influencer and talent contracts. Add AI disclosure clauses. Clarify who is responsible for compliance: the brand, the agency, or the talent.
Train your team. Make sure everyone involved in ad production understands the new requirements. This includes in-house creatives, agency partners, and freelancers.
Monitor the federal landscape. Track the White House AI Framework and any preemption developments. Adjust your compliance strategy as the regulatory picture evolves.

How MKDM Can Help

I work with businesses to audit their marketing workflows and build compliance processes that don't slow down production. For this specific law, that means mapping your AI touchpoints, creating disclosure templates that meet the legal standard without cluttering your creative, and updating your team's processes before the June 9 deadline. If you're running AI-assisted advertising (and statistically, you probably are), it's worth getting this right before enforcement begins. Reach out and I can walk through what your specific workflow needs.

For a broader look at how AI is reshaping advertising strategy, see my AI Advertising: The Complete Guide for 2026.

Frequently Asked Questions

What does New York's AI advertising disclosure law require?

The law requires advertisers to clearly disclose when commercial ads feature AI-generated content or synthetic performers, including digital doubles of real people. Disclosures must be visible and understandable to consumers before they engage with the ad. This applies to images, video, text, and any AI-generated likeness used in commercial contexts.

When does the New York AI ad disclosure law take effect?

The AI Transparency in Advertising and Synthetic Performer Disclosure Law takes effect on June 9, 2026. Businesses running AI-generated advertising that reaches New York audiences should have compliance processes in place before that date to avoid potential enforcement actions.

Does this law apply to businesses outside of New York?

If your ads reach New York consumers, you likely need to comply regardless of where your business is headquartered. The law targets commercial advertising shown to New York audiences, not just businesses physically located in the state. For national digital campaigns, assume New York is in scope.

What counts as a synthetic performer under the law?

A synthetic performer is an AI-generated likeness of a real or fictional person used in advertising. This includes digital doubles (AI replicas of real individuals), AI-generated models, and any deepfake-style representations used in commercial content. The definition is broad enough to cover most AI-generated human likenesses in ads.

How should disclosures be formatted in ads?

The law requires disclosures to be clear and visible to consumers. While specific formatting requirements may vary, best practices from the IAB framework suggest using plain-language labels like "AI-generated image" or "Features a synthetic performer" placed prominently within the ad, not buried in fine print or behind a click. The disclosure should be visible before the consumer engages with the AI-generated content.

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Meaningful Retirement Gifts That Last Forever

Matt Kundo — Wed, 01 Apr 2026 10:04:15 +0000

The Problem with Traditional Retirement Gifts

Nearly three-quarters of adults over 50 say personal gifts matter more than expensive ones. Yet most retirement gift ideas fall into the same predictable categories: desk accessories, experience vouchers, or cash contributions to a group gift. These are nice gestures but not incredibly meaningful ones.

The issue is not effort. People genuinely want to honor the retiree. The issue is that most retirement gifts are designed around the occasion, not the person. A plaque, a gift card, a nice watch: these acknowledge the milestone, but none of them say anything.

Every year, millions of people close a chapter that defined their identity for decades. The transition from working professional to retiree is not just logistical. It is emotional. And the right retirement gift should honor that.

Why a Personal Documentary Is the Retirement Gift That Lasts

A personal documentary does something no other retirement gift can: it turns a career, a personality, and a lifetime of stories into a film that the whole family can watch, share, and keep forever.

Think about what gets lost when someone retires. The colleagues who knew them best scatter. The daily routines that shaped their identity disappear. The stories they told at lunch, the lessons they shared in hallways, the personality they brought to every meeting: all of it fades into memory.

A documentary preserves those things. It captures the retiree's voice. Their perspective. The way they laugh when they tell a story about something that happened in 1998. These are the details that families treasure most, and they are the details that no material gift can replicate.

There is a concept in gerontology called "life review," the idea that structured storytelling in later life helps people find meaning and integrate their life narrative. A personal documentary is life review at its best: guided, cinematic, and permanent.

What a BioPic Retirement Documentary Looks Like

The process is simpler than most people expect.

You share the photos, home videos, and stories that matter most. Old career milestones, family vacations, the candid moments that capture who the retiree really is. You do not need to organize everything perfectly. Just gather what you have.

BioPic Studios takes those materials and crafts them into a short documentary with cinema-quality storytelling. Their filmmakers build a narrative arc, select the most powerful moments, add professional editing and scoring, and deliver a finished film. No filming is required on your end.

The result is not a slideshow of photos set to music. It is a film that feels like it belongs on a streaming platform. Every project comes with a 100% satisfaction guarantee.

Who Gives a Documentary as a Retirement Gift

This is the kind of gift that comes from people who know the retiree well enough to want more than a gesture.

Adult children honoring a parent's career. After watching a parent work their entire life, a documentary says something a gift card never could: we paid attention. We saw what you built. Your story is worth preserving.

Spouses marking a shared milestone. Retirement changes the shape of a marriage. A documentary about the retiree's career, or about the couple's life together, gives both partners something to hold onto as the next chapter begins.

Colleagues and teams saying goodbye. A workplace documentary that captures the retiree's impact, told through the memories of the people who worked alongside them, is a farewell gift that no one forgets.

The Retirement Gift That Gets More Valuable Over Time

Most retirement gifts lose their meaning within weeks. The watch finds a home in a drawer. The experience voucher runs its course. These are decent gifts, but they fade.

A documentary does the opposite. It becomes more valuable with time. Five years after retirement, the family rewatches it and notices details they missed the first time. Ten years later, it becomes a piece of family history. Twenty years later, when the retiree's grandchildren want to know what their grandparent was like in their prime, the documentary is there.

How to Give a BioPic Documentary as a Retirement Gift

Start with the story. What defined this person's career? What are the stories their family and colleagues tell about them? What do you want preserved?

Gather the materials. Photos, home videos, career milestones, personal moments. Pull from phone galleries, old albums, and boxes of prints. You do not need to curate it. Just collect it.

Reach out. Visit gift.biopicstudios.com or start the process at story.biopicstudios.com. BioPic's team will guide you through the rest.

Common Questions About Documentary Retirement Gifts

What if the retiree is private and would not want to be filmed? No filming is required. BioPic builds documentaries from the materials you share: photos, home videos, career milestones, stories from family and colleagues.

How much does a retirement documentary cost? BioPic offers Hollywood production values at accessible prices, with options starting in the hundreds. Visit gift.biopicstudios.com for current pricing.

Retirement Marks the End of a Career. Not the End of a Story.

The most meaningful retirement gifts are not the ones that cost the most. They are the ones that say something true about the person receiving them.

A personal documentary from BioPic Studios says: your career mattered. Your stories deserve to be heard. The life you built is worth preserving on film.

Originally published at biopicstudios.com

Google Loyalty Ads Hit AI Mode: What Marketers Should Do Now

Matt Kundo — Wed, 01 Apr 2026 10:04:03 +0000

Google Loyalty Program Ads AI Mode: A New Retention Channel Just Opened Up

On March 25, 2026, Google quietly rolled out one of the more consequential Shopping updates this year: loyalty program benefits now surface in AI Mode and Gemini, not just traditional product listings. Retailers who have configured member pricing and shipping in Merchant Center now get their loyalty perks displayed directly inside AI-powered shopping conversations. That's a significant distribution upgrade, considering AI Mode processes over 75 million daily queries. If you run any kind of loyalty or membership program and advertise through Google, this changes your priority list.

What Happened

Google expanded its Merchant Center loyalty program features to 14 countries and AI-first surfaces on March 25, 2026. The rollout covers Australia, Brazil, Canada, France, Germany, India, Italy, Japan, Mexico, Netherlands, South Korea, Spain, the United Kingdom, and the United States.

The update introduces two key capabilities. First, merchants can now showcase member pricing (exclusive discounts displayed via the loyalty_program attribute) and member shipping (special delivery options using the shipping_label attribute) directly in product listings. Second, and more importantly, these loyalty benefits now appear on AI-first surfaces including AI Mode and Gemini, marking the first time loyalty data has been integrated into Google's conversational shopping experience. The feature also extends to local inventory ads and regional Shopping ads, broadening reach for brick-and-mortar retailers with loyalty programs.

Why This Matters for Your Marketing

Google Shopping and PPC Impact

Google reports that retailers using personalized loyalty ads are seeing up to a 20% increase in click-through rates. That number makes sense. When a shopper sees strikethrough pricing with a "member price" badge next to a standard listing, the visual differentiation is immediate. For advertisers already running Shopping campaigns, this is incremental CTR without additional spend. You just need the loyalty program configured correctly in Merchant Center and a Customer Match list connected in Google Ads.

AI Mode Visibility

This is where the update gets interesting. AI Mode is quickly becoming a primary shopping surface. Google's VP of Ads and Commerce, Vidhya Srinivasan, has positioned 2026 as the year AI Mode ads move from experimental to core placements. Loyalty program data appearing in these conversational results means your products get presented with richer context (pricing tiers, member benefits, exclusive shipping) during the exact moment a shopper is evaluating options. That's a fundamentally different touchpoint than a standard Shopping grid.

Customer Retention Strategy

Most loyalty programs live in email sequences and app notifications. Google just gave those programs an acquisition and retention surface inside search. A potential customer who sees "Members save 15%" in an AI Mode recommendation has a reason to both purchase and join the program. This turns a retention tool into a top-of-funnel differentiator. For SMBs competing against larger retailers, a well-configured loyalty program in Merchant Center can now punch above its weight in visibility.

Google Loyalty Program Ads AI Mode: Your Action Plan

Activate the loyalty program add-on in your Google Merchant Center account. Navigate to Growth > Loyalty program and enable it.
Define your program tiers and benefits. Add the specific member pricing and shipping perks for each tier. Be concrete: "$5 off orders over $50" works better than vague "member discounts."
Configure the loyalty_program attribute in your product feed. This controls how member pricing displays, including the strikethrough format that drives clicks.
Set up the shipping_label attribute for products eligible for member shipping benefits. Map this to your actual fulfillment capabilities.
Connect your Customer Match list in Google Ads. This is required for full strikethrough pricing visibility and member shipping badges to appear.
Verify your local inventory feed if you have physical locations. The expansion to local inventory ads means in-store loyalty perks can now surface in local searches.
Audit your existing Shopping campaigns for products where loyalty pricing creates the biggest competitive gap. Prioritize high-margin items where member discounts still maintain healthy returns.
Monitor AI Mode performance separately. As these placements scale, you'll want to track how loyalty-enhanced listings perform in conversational contexts versus traditional Shopping grids.

How I Can Help

Setting up loyalty program ads correctly involves coordination between your Merchant Center feed, Google Ads Customer Match lists, and your actual loyalty program infrastructure. I work with businesses to configure these integrations properly from the start, so you're not troubleshooting feed errors while your competitors are collecting clicks. If you're running Google Shopping campaigns and have any kind of membership or loyalty program, even a simple email-based discount tier, this update is worth acting on quickly.

Frequently Asked Questions

What are Google loyalty program ads in AI Mode?

Google loyalty program ads in AI Mode display member-exclusive pricing and shipping benefits directly within AI-powered shopping conversations. When users ask product questions in AI Mode, loyalty benefits appear alongside organic recommendations, giving participating retailers a visibility advantage over competitors without loyalty programs configured.

How do I set up loyalty program ads in Google Merchant Center?

Activate the loyalty program add-on in Google Merchant Center, add your program details including member tiers and benefits, then configure member pricing using the loyalty_program attribute and member shipping using the shipping_label attribute. You also need a Customer Match list connected in Google Ads for full strikethrough pricing and member shipping badge visibility.

Which countries support Google loyalty program ads?

As of March 2026, Google loyalty program ads are available in 14 countries: Australia, Brazil, Canada, France, Germany, India, Italy, Japan, Mexico, Netherlands, South Korea, Spain, United Kingdom, and United States. Google has not announced a timeline for additional country support.

Do loyalty program ads improve click-through rates?

According to Google's data, retailers using personalized loyalty program ads have seen up to a 20% increase in click-through rates compared to standard product listings. The member pricing strikethrough format and exclusive shipping badges create visual differentiation that draws more clicks in both traditional Shopping results and AI Mode conversations.

Originally published at mattkundodigitalmarketing.com

Veo in Google Ads: How to Use AI Video for Better Campaigns

Matt Kundo — Mon, 30 Mar 2026 17:20:44 +0000

Veo Google Ads AI Video Generation: What Changed and Why It Matters

Google just put a video production studio inside every Google Ads account. As of March 29, 2026, the Veo generative video model is live in Asset Studio, and it does something that would have cost most small businesses thousands of dollars a year ago: it turns your static product images into 10-second video ads with natural, fluid motion. No camera crew. No editing software. No production timeline. For businesses running Demand Gen or YouTube campaigns, this is a meaningful shift in how you create and test video creative.

What Happened

Google rolled out Veo globally inside Google Ads Asset Studio on March 29, 2026, as part of a broader Demand Gen product update. The tool lets advertisers upload one to three static images and generates unique 10-second video clips from each, complete with natural motion effects optimized for YouTube formats.

This follows the earlier rollout of Nano Banana Pro, Google's AI image generator for background swaps and visual adaptations. Together, they form a creative toolkit that lives entirely inside the ad platform. According to Search Engine Land's coverage, early testers like Ameet Khabra (founder of Hop Skip Media) reported strong results for consumer product brands, noting that "consumer product brands with clean imagery and inherent motion logic will get the most out of this."

The generated videos can be packaged into customizable ad templates and deployed across YouTube, YouTube Shorts, Discover, and Gmail placements. Google's own data shows that Demand Gen campaigns with at least three unique videos demonstrate stronger lifts in brand consideration and purchase intent.

Why This Matters for Your Marketing

Video Ads Without the Production Budget

The biggest barrier to video advertising for small and mid-sized businesses has always been production cost. A basic product video shoot can run $2,000 to $10,000 depending on quality and complexity. Veo removes that barrier entirely. If you have clean product photography (which most e-commerce brands already do), you now have the raw material for video ads. The playing field between large brands with dedicated creative teams and lean operations running on tight budgets just got significantly more level.

Demand Gen Gets a Creative Boost

Demand Gen campaigns perform best with creative variety. Google has been pushing this point for months: more asset variations mean more combinations for the algorithm to test, which means better optimization over time. Veo makes it practical to maintain that variety. Instead of commissioning new video creative every quarter, you can generate multiple variations from your existing image library, test them, and iterate based on performance data. This also helps push your Ad Strength rating toward "Excellent," which Google's system rewards with better delivery.

The AI Creative Arms Race in Paid Media

This is part of a larger pattern. Google, Meta, and other ad platforms are all embedding generative AI tools directly into their campaign builders. The goal is to keep creative production inside the platform ecosystem, reduce friction, and give the algorithms more creative inputs to optimize against. Advertisers who adopt these tools early will have a testing advantage. Those who wait will find themselves competing against accounts with 10x the creative variety and no additional production cost. My take: this is not optional to explore. Even if Veo-generated video doesn't replace your hero content, it will absolutely work for testing hooks, formats, and audience segments at low cost.

Action Plan: How to Start Using Veo in Google Ads

Check your Asset Studio access. Log into Google Ads and navigate to Asset Studio. Veo should be available globally as of March 29, 2026. If you don't see it, check that your account is on the latest interface version.
Audit your product image library. Veo works best with clean, high-resolution product images on neutral or simple backgrounds. Round up your top 10-15 product shots and assess which ones have "inherent motion logic" (products that look natural in motion).
Generate your first batch of test videos. Upload your three strongest images and let Veo create video variations from each. Review the output for quality and motion naturalness before deploying.
A/B test Veo videos against static images in Demand Gen. Run a split test with identical targeting. Compare CTR, view rate, and conversion metrics between static image assets and Veo-generated video assets over a two-week window.
Test 10-second Veo clips as YouTube bumper ads. Bumper ads (6 seconds) and short in-stream formats are a natural fit for the 10-second clips Veo produces. Trim or let Google auto-adapt them for bumper placements.
Pair Veo with Nano Banana for audience-specific variations. Use Nano Banana to swap backgrounds or adjust visual context for different audience segments, then generate Veo videos from those adapted images. This gives you personalized video creative at scale.
Update your creative refresh cadence. With production costs near zero, there is no reason to run the same video creative for months. Plan for bi-weekly or monthly creative refreshes using Veo-generated content.
Track AI-generated vs. traditional video performance. Tag your Veo-generated assets so you can compare their performance against any traditionally produced video content in your account.

How MKDM Can Help

I work with businesses on Google Ads campaign strategy and management, including creative testing frameworks that take advantage of tools like Veo. If you are running Demand Gen or YouTube campaigns and want to build a structured approach to AI-generated video creative, I can help you set up the testing framework, analyze results, and scale what works. The technology is accessible, but knowing how to test and iterate on it strategically is where the real value sits. Get in touch if you want to put Veo to work for your campaigns.

Frequently Asked Questions

What is Veo in Google Ads?

Veo is Google's generative AI video model, now integrated into Google Ads Asset Studio. It lets advertisers upload up to three static images and automatically generates 10-second video ads with natural motion, optimized for YouTube and Demand Gen campaigns. The tool is designed to make video ad creation accessible to businesses without dedicated video production resources.

Do I need video production experience to use Veo?

No. Veo handles the video generation process automatically. You upload static product images, and the AI creates video clips with fluid motion. From there, you can customize using templates inside Asset Studio before deploying to your campaigns. The main requirement is having quality source images to work from.

Which Google Ads campaign types support Veo video ads?

Veo-generated videos work with Demand Gen campaigns (across YouTube, YouTube Shorts, Discover, and Gmail) and Performance Max campaigns. They are optimized for YouTube ad formats including bumper ads and in-stream placements. Google is also testing AI-generated animated clips inside PMax as a related feature.

How long are the videos Veo creates?

Veo generates video clips up to 10 seconds long from each uploaded image. You can generate multiple unique clips from different source images, giving you a library of short-form video assets to package into ad templates for testing and rotation across campaigns.

Is Veo available to all Google Ads accounts?

Yes. As of March 2026, Veo is available globally inside Google Ads Asset Studio. Any advertiser with a Google Ads account can access it through the asset creation workflow. No beta signup or waitlist is required. If you are managing Google Ads campaigns, you can start generating video assets today.

Originally published at mattkundodigitalmarketing.com

Google PMAX Audience Exclusions: What Advertisers Need Now

Matt Kundo — Mon, 30 Mar 2026 17:20:15 +0000

Google PMAX Audience Exclusions: What Advertisers Need Now

Google just gave PMAX advertisers the control they have been requesting for years. After months of complaints about wasted spend on existing customers and irrelevant audiences, Google Ads Performance Max now supports audience exclusions at the campaign level. This isn't just another minor platform tweak—it's a fundamental shift that finally lets SMB advertisers stop throwing money at audiences who already converted or never will.

For businesses running Performance Max campaigns, this update addresses the most frustrating limitation: watching your budget disappear on repeat conversions from existing customers while struggling to reach new prospects. The new exclusion controls, combined with enhanced reporting features, give you the steering wheel you've been missing in Google's automated campaign type.

What Happened

Google announced significant updates to Performance Max in late March 2026, introducing first-party audience exclusions alongside expanded reporting capabilities. The rollout began March 26th and is now live across all Google Ads accounts.

The headline feature allows advertisers to exclude customer match lists directly within PMAX campaigns, shifting budget allocation from repeat conversions toward net-new customer acquisition. According to Search Engine Land's coverage, this addresses advertiser demands for greater transparency and control in automated campaigns.

Accompanying this change are enhanced reporting tools including budget forecasting, detailed demographic breakdowns, and network-level performance segmentation. As Search Engine Journal reported, these updates position Performance Max as more manageable for advertisers who want intentional campaign optimization rather than complete automation.

The timing aligns with Google's broader algorithm updates this month, as noted by PPC Land's analysis of the platform's recent changes.

Why This Matters for Your Marketing

Budget Efficiency for SMBs

Small and medium businesses waste 15-25% of their Performance Max budget on existing customers according to recent optimization studies. With audience exclusions, you can upload your customer database and prevent PMAX from targeting people who already bought from you. This simple change typically improves return on ad spend by 10-20% in acquisition-focused campaigns.

The impact is particularly significant for subscription services, e-commerce brands, and service providers who need to prioritize new customer acquisition over retention advertising. Instead of competing with your email marketing and loyalty programs for the same customers, PMAX can focus its machine learning on finding similar prospects.

Better Targeting Control

Performance Max's "black box" approach has frustrated advertisers since launch. The new exclusion features provide directional steering without sacrificing automation benefits. You can now exclude demographics (age and gender), customer segments, and low-performing audiences while letting Google's algorithm optimize within those constraints.

This matters most for businesses with clear customer personas or geographic limitations. A luxury retailer can exclude audiences under 25, while a local service provider can focus budget on their service area without wasting spend on distant prospects.

Improved Campaign Transparency

The enhanced reporting tools solve Performance Max's biggest weakness: lack of visibility into where your money goes. Budget forecasting shows projected end-of-month spend and simulates the impact of daily budget changes. Network segmentation breaks down performance across Search, YouTube, Display, and Discovery, enabling smarter optimization decisions.

This transparency helps justify Performance Max investment to stakeholders and enables data-driven budget allocation across campaigns and channels.

Action Plan Checklist

  1. Audit your current PMAX campaigns for audience overlap with existing customers and identify wasted spend patterns using the new demographic reporting tools.


Build exclusion lists starting with your customer database, past purchasers from the last 90 days, and any email subscribers who recently converted.
Review demographic performance and exclude age groups or genders that consistently underperform relative to your target customer profile.
Set up budget forecasting to monitor projected monthly spend and test daily budget adjustments based on the new simulation tools.
Implement network-level optimization by analyzing the expanded reporting to identify which Google networks deliver the best ROI for your business.
Create testing frameworks to measure the impact of exclusions on acquisition costs and overall campaign performance before and after implementation.
Update your PMAX strategy to separate prospecting and retention efforts, allowing specialized campaigns to handle each objective more effectively.
Monitor data quality in your customer match lists to ensure exclusions remain accurate as your customer base evolves.

How MKDM Can Help

I help businesses optimize their Performance Max campaigns using these new audience exclusion controls, turning Google's platform updates into competitive advantages for SMB advertisers. My Google Ads management services include PMAX audit and optimization, exclusion list development, and performance monitoring to maximize your return on ad spend.

If you're running Performance Max campaigns and want to implement these new controls effectively, I can analyze your current setup, identify optimization opportunities, and build exclusion strategies that align with your business goals. The key is understanding which audiences to exclude without limiting your campaign's learning and reach potential.

Ready to stop wasting budget on the wrong audiences? Contact me to discuss how these PMAX updates can improve your advertising performance and reduce acquisition costs.

FAQs

Q: Will excluding audiences hurt my Performance Max campaign's machine learning?

A: No, Google designed these exclusions to work within PMAX's automation. You're providing directional steering rather than restrictive targeting. The algorithm still learns and optimizes, but within the boundaries you set. Think of it as setting guardrails, not building walls.

Q: How do I know which audiences to exclude from Performance Max?

A: Start with your existing customer lists, then use the new demographic reporting to identify consistently underperforming segments. Look for age groups or genders with high cost per acquisition relative to your target metrics. Avoid excluding broad audiences initially—start specific and expand based on performance data.

Q: Can I still use audience signals with the new exclusion features?

A: Yes, audience signals and exclusions work together. Signals guide the algorithm toward valuable prospects while exclusions prevent targeting unwanted segments. This combination gives you both positive and negative steering controls for more precise campaign optimization.

Q: Do PMAX audience exclusions affect other campaign types?

A: No, Performance Max exclusions are campaign-specific and don't impact Search, Display, or other campaign types. However, account-level negative keywords still affect all campaigns including PMAX, so use campaign-level controls for PMAX-specific optimizations.

Q: How often should I update my PMAX exclusion lists?

A: Review customer exclusion lists monthly to add new converters and remove prospects who might convert in the future. Demographic exclusions need less frequent updates—quarterly reviews are typically sufficient unless your business model or target audience changes significantly.

Q: What's the minimum customer list size needed for PMAX exclusions?

A: Google's Customer Match requires at least 1,000 active users in most countries, though this can vary by region. For exclusion purposes, even smaller lists provide value by preventing spend on known converters, but larger lists offer more comprehensive protection against wasted budget.

Originally published at mattkundodigitalmarketing.com

Google March 2026 Core Update: What Marketers Should Do Now

Matt Kundo — Sun, 29 Mar 2026 10:02:12 +0000

Google March 2026 Core Update: What Marketers Should Do Now

Google confirmed its March 2026 core update began rolling out on March 27, 2026 at approximately 2:00 AM Pacific Time. This comes just two days after the March 2026 spam update completed its rollout in a record-breaking 20 hours. Two major algorithm changes in the span of a week is unusual, and it means organic search rankings are in flux right now. If your business depends on Google for leads, traffic, or revenue, the next two weeks matter. This is not a spam penalty. It is a broad quality recalibration, and understanding the difference will determine how you respond.

What Happened with the Google March 2026 Core Update

The March 2026 spam update launched on March 24 and was fully rolled out by March 25, making it the fastest spam update in Google's Search Status Dashboard history. It targeted existing spam policies (cloaking, link spam, scaled content abuse, expired domain abuse) using evolved SpamBrain systems. No new policies were introduced.

Then, on March 27, Google began the March 2026 core update. This is the first broad core update of 2026, affecting search rankings worldwide across all languages. Google described it as 'a regular update designed to better surface relevant, satisfying content for searchers from all types of sites.' The rollout is expected to take approximately two weeks.

Why This Matters for Your Marketing

SEO and Organic Traffic

Core updates recalibrate how Google evaluates content quality across the entire index. Rankings now hinge on comparative value across competing pages, with stronger emphasis on E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness). Sites with thin or derivative content historically see traffic drops of 20-50% during core updates. Sites investing in original, expert-driven content tend to gain visibility.

Content Marketing

The back-to-back spam and core updates send a clear signal: Google is getting more aggressive about content quality in 2026. The spam update specifically targeted scaled content abuse, which includes AI-generated content published at volume without meaningful human editorial input. The core update reinforces this by rewarding content that demonstrates genuine expertise.

Paid Search and Budget Allocation

During core update rollouts, organic rankings become unpredictable. This creates a temporary window where paid search becomes more important for maintaining visibility on critical keywords. If you see organic positions dropping for high-value terms, consider increasing PPC budgets on those keywords as a stopgap while the update settles.

Local SEO

Core updates affect all search results, including local queries. If your business appears in local pack results or depends on 'near me' searches, monitor your GEO and SEO performance closely. Changes to how Google evaluates page quality can shift which pages appear for local intent queries.

E-Commerce and Product Pages

Product pages and category pages are often vulnerable during core updates because they tend to be thin on unique content. Focus on adding original product insights, comparison context, and genuine buying guidance that differentiates your pages from competitors.

Action Plan: What to Do Right Now

Benchmark your current rankings today. Export your Google Search Console performance data for the past 28 days.
Do not make reactive changes. Avoid restructuring pages, deleting content, or making major technical changes during the rollout.
Audit your lowest-performing content. Identify pages with high impressions but low click-through rates.
Check for thin content patterns. Review pages under 500 words and pages with duplicate content.
Strengthen E-E-A-T signals. Update author bios, add credentials, cite authoritative sources.
Review your AI content. Evaluate whether it includes genuine editorial input and unique insights.
Monitor daily, but decide weekly. Check Search Console daily but hold strategic decisions until after rollout.
Document everything. Keep a log of ranking changes by page and keyword.

How I Can Help

I run SEO audits specifically designed to identify vulnerabilities during core updates. That means analyzing your content quality against the pages currently outranking you, identifying E-E-A-T gaps, and building a prioritized action plan based on what Google is actually rewarding right now. Reach out for a consultation at /contact/.

Frequently Asked Questions

What is the Google March 2026 core update?

The Google March 2026 core update is a broad algorithmic change that began rolling out on March 27, 2026. It recalibrates Google's ranking systems to better surface relevant, high-quality content across all website types and languages. The rollout is expected to take approximately two weeks.

How long will the March 2026 core update take to roll out?

Approximately two weeks, based on historical patterns. The December 2025 core update took 18 days. Monitor progress on Google's Search Status Dashboard.

Should I make changes to my website during the core update rollout?

Avoid making major structural changes during the rollout. Focus on documenting ranking changes, auditing content quality, and preparing improvements to implement after the update completes.

What is the difference between the spam update and core update?

The spam update (March 24-25) targeted policy violations using SpamBrain. The core update (March 27) is a broader quality recalibration based on relevance, helpfulness, and E-E-A-T. The spam update penalizes bad actors; the core update rewards quality.

How do I know if my site was affected?

Check Google Search Console for changes in impressions, clicks, and average position starting March 27. Significant drops (over 20%) suggest the update affected your rankings.

Originally published at mattkundodigitalmarketing.com

LinkedIn Marketing Benchmarks: CTR, Engagement, and What They Mean

Matt Kundo — Thu, 26 Mar 2026 10:02:55 +0000

Most marketers track their LinkedIn numbers without any real sense of whether those numbers are good. You see a 0.5% click through rate on LinkedIn and think, "Is that decent? Should I panic?" The honest answer is that it depends, but not in the vague, unhelpful way you might expect. There are real benchmarks you can measure against.

LinkedIn now commands 41% of all B2B advertising budgets, and the platform delivered a 121% return on ad spend in 2025. Those numbers make it clear that LinkedIn is not just another social channel. It is the B2B advertising platform. But if you are spending money there (or investing time in organic content), you need to know what good performance actually looks like.

This guide breaks down the real click through rate benchmarks for LinkedIn ads and organic content in 2026, organized by format, industry, and content type. We pulled data from six major benchmark reports so you do not have to. Whether you are running paid campaigns or building organic reach, you will walk away knowing exactly where your click through rate on LinkedIn stands and what to fix.

What Is a Good Click Through Rate on LinkedIn? The Short Answer

The median CTR across all LinkedIn ad formats and industries is about 0.52%, according to benchmark data from Closely HQ. But that median hides a wide range of performance. Here is how to think about where your campaigns fall:

Excellent (Above 1.15%): Top-tier targeting and creative. Typical of ABM campaigns at enterprise companies.
Good (0.65% to 1.15%): Above average. Your targeting and messaging are resonating.
Average (0.44% to 0.65%): Right in the middle. Not broken, but room to grow.
Below Average (0.30% to 0.44%): Targeting or creative needs attention.
Poor (Below 0.30%): Something is fundamentally off with audience, offer, or creative.

The important context: account-based marketing (ABM) campaigns average a 1.15% CTR based on analysis of 161,256 ads from 211 companies. Enterprise companies with $1B+ revenue hit even higher at 1.91%. So if you are running tightly targeted ABM campaigns, your bar is higher than the general average.

There is also a practical threshold worth knowing. Campaigns that achieve above a 0.7% click through rate on LinkedIn see roughly 15% lower cost per click. The algorithm rewards engagement, so better CTR literally saves you money.

LinkedIn Ad CTR Benchmarks by Format

Not all LinkedIn ad formats produce the same click through rate on LinkedIn. The format you choose sets the baseline for what "good" looks like. Here is what the data shows for each major format in 2026.

Video Ads

Video is where the growth is happening. LinkedIn video ads saw 52% year-over-year growth in views and now account for 28% of total ad impressions on the platform. Videos under 15 seconds with bold opening hooks consistently outperform longer formats.

The key advantage of video is not just CTR. Video ads generate higher engagement overall, which feeds the algorithm and extends your reach. If you are not testing video on LinkedIn yet, you are leaving performance on the table.

Carousel Ads

Carousel ads outperform static image ads for storytelling and multi-step narratives. They work especially well for showcasing multiple products, walking through a process, or presenting data in digestible slides.

Message Ads play by different rules. Instead of CTR, the primary metric is open rate, which exceeds 50% on average. That is dramatically higher than email marketing open rates. Message Ads work best for direct offers, event invitations, and high-value content where personalization matters.

Text Ads

Text Ads typically have the lowest CTR of any LinkedIn format, but they also have the lowest cost. They are best used as a supplementary format alongside Sponsored Content. They work well for retargeting campaigns where the audience already knows your brand.

LinkedIn CTR Benchmarks by Industry

Your industry plays a major role in what a good click through rate on LinkedIn looks like. A 0.60% CTR might be excellent in engineering but only average in education. Here are the 2026 benchmarks:

Business Development: 0.65%
Education: 0.65%
Accounting: 0.60%
Finance: 0.60%
Engineering: 0.57%

Why do some industries outperform others? It comes down to audience engagement patterns. Industries where professionals actively seek solutions on LinkedIn (business development, education) naturally see higher click through rates. Engineering audiences, by contrast, tend to engage more selectively.

Company size also matters. Companies with $1B+ revenue achieve a 1.91% CTR in ABM campaigns, compared to smaller firms. Larger companies typically have bigger budgets for creative testing, more sophisticated targeting, and stronger brand recognition that lifts engagement.

If your industry is not listed above, use the general benchmarks as your starting point. A CTR above 0.65% puts you in good territory regardless of vertical.

Organic LinkedIn Engagement Benchmarks

Paid ads are only half the picture. Organic content plays a huge role in your overall LinkedIn performance. The overall average organic engagement rate sits at 5.20%, up 8% year over year.

Engagement by Content Type

Native Document (PDF/Slides): 7.00% (+14% YoY)
Video: 5.60% to 6.00% (+7% YoY)
Image Post: 4.85% to 5.30% (+9% YoY)
Text Post: 4.00% to 4.50% (+12% YoY)
Link Post: 3.30% (Flat)

The takeaway is clear. Native documents (PDFs, slide decks uploaded directly) are the top performers by a wide margin. Link posts, where you share an external URL, generate the lowest engagement because the algorithm deprioritizes content that sends users off-platform.

Personal Profiles vs Company Pages

One of the most striking LinkedIn benchmarks: personal profiles outperform company pages by 561%. The algorithm favors individual voices over corporate messaging. People engage with people, not logos.

How LinkedIn Compares to Other Platforms

The visitor-to-lead conversion rate on LinkedIn is 2.74%, which is 277% higher than Facebook (0.77%) and nearly four times Twitter/X (0.69%). For B2B marketers, this makes LinkedIn the highest-converting social platform by a significant margin.

On the advertising side, LinkedIn ROAS sits at 121%, compared to Google Search at 67% and Meta at 51%. LinkedIn is not just generating clicks. It is generating revenue.

What Is Dragging Your LinkedIn CTR Down? Common Mistakes

If your click through rate on LinkedIn is below the benchmarks above, the fix is usually not complicated:

Targeting too broadly. Layer job title, seniority, company size, and industry for tighter audiences.
Not refreshing creatives. Ad fatigue sets in fast. Refresh every 14 days.
Overly complex Lead Gen Forms. Keep forms short: name, email, company, and one qualifying question at most.
Generic messaging. Create audience-specific messaging that addresses specific pain points.
Ignoring retargeting. Warm audiences click at two to four times the rate of cold audiences.
Sending traffic to slow pages. Even a strong CTR is wasted if your landing page does not convert.

How to Improve Your LinkedIn Click Through Rate

Targeting Optimization

Precise targeting is the single biggest lever. Retargeting audiences of 500 to 5,000 users yield 800% ROI, and matched audience lists of 1,000 to 10,000 cut cost per lead by 30% to 50%.

Creative Best Practices

Short video (under 15 seconds) with a bold visual hook in the first two seconds consistently outperforms other formats. Keep headlines under 100 characters. Test at least three to five creative variations. The 14-day refresh cycle should be built into your content calendar.

Landing Page Alignment

Native Lead Gen Forms convert at 6% to 10%, roughly double the 3% to 5% you will see with external landing pages. Use them whenever your goal is lead capture. For offers that require more explanation, make sure your landing page copy directly mirrors the language in your ad.

How to Track and Measure LinkedIn Performance

The metrics that matter:

CTR: Target above 0.7% for ad relevance and lower CPC
CPC: $3.94 median across LinkedIn ads
CPM: $68.62 average for reach efficiency
CPL: $128 average lead acquisition cost
Conversion Rate: 2-5% (landing page), 6-10% (Lead Gen Form)

LinkedIn Conversions API (CAPI) is increasingly important for accurate measurement. Companies using CAPI see a 20% reduction in CPA and 31% more attributed conversions.

The Bottom Line

What is a good click through rate on LinkedIn? It depends on your ad format, your industry, whether you are running paid or organic campaigns, and how precisely you have targeted your audience. But the benchmarks are clear: aim for above 0.7% CTR on paid campaigns to hit the efficiency sweet spot, and prioritize native content formats for organic engagement.

The companies seeing the best results on LinkedIn are doing three things well. They target precisely, refresh creatives frequently, and measure performance against actual business outcomes rather than vanity metrics.

Originally published at mattkundodigitalmarketing.com

Google March 2026 Spam Update: SEO Impact and What to Do Now | MKDM

Matt Kundo — Wed, 25 Mar 2026 13:20:55 +0000

Home / Blog / March 2026 Spam Update Recent News & SEO Mar 25, 2026 7 min read Google March 2026 Spam Update: SEO Impact and What to Do Now

Google launched its March 2026 spam update on March 24, targeting spam policy violators through SpamBrain improvements. Here's what marketers need to know and do right now to protect their rankings.

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Google's March 2026 Spam Update Is Already Rolling Out: What the SEO Impact Means for Your Business

Google launched its first spam update of 2026 on March 24 at 12:18 PM PDT, and the rollout is moving faster than anyone expected. While the August 2025 spam update took nearly four weeks to complete, Google estimates this one will wrap up in days, possibly by March 27 or 28. That compressed timeline matters. If your site has any spam policy exposure, the window to act before rankings shift is measured in hours, not weeks. For businesses that depend on organic search traffic, this is the moment to verify compliance rather than wait and react.

What Happened: Google March 2026 Spam Update SEO Impact Timeline

Google confirmed the March 2026 spam update through its Search Status Dashboard at 12:18 PM PDT on March 24, followed by an announcement on the Google Search Central LinkedIn page two minutes later. The post drew 587 reactions, 24 comments, and 138 reposts within hours, signaling the SEO community's attention level.

This is a global update affecting all languages and regions. It runs on SpamBrain, Google's AI-powered spam detection engine, which has been refined to better identify sophisticated manipulation tactics. Unlike a core update that changes how Google broadly evaluates content quality, this update specifically enforces existing spam policies. No new policies were added, similar to the approach taken with the December 2024 spam update that completed in seven days.

SERP tracking tools including Semrush and Wincher are already reporting elevated volatility across multiple verticals, consistent with an active rollout.

Why This Matters for Your Marketing

SEO Rankings at Risk

SpamBrain's improvements target several categories of spam that remain common across the web: thin content designed to rank rather than inform, link schemes built on paid or manipulated backlinks, cloaking (showing different content to search engines than to users), expired domain abuse, and site reputation abuse (sometimes called parasite SEO). If your site or any third-party content hosted on your domain falls into these categories, rankings could drop significantly or pages could be deindexed entirely. Historical data from prior spam updates shows affected sites losing 40% to 90% of organic traffic within days of rollout completion.

Content Quality Standards

The update specifically targets scaled content abuse, which includes mass-produced AI-generated pages created to manipulate rankings. This does not mean all AI-assisted content is at risk. Google's distinction remains clear: content that provides genuine value to users, regardless of how it was produced, aligns with policy. Content that exists primarily to game search results does not. SEO analyst Lily Ray predicted a 2026 crackdown on AI-generated spam back in December 2025, comparing it to the severity of the March 2024 core update, Penguin, and Panda. This update appears to be that enforcement moment.

Link Profile Health

Unnatural link building remains a primary target. If your SEO strategy has relied on purchased links, private blog networks, or large-scale link exchanges, this update increases the risk of those tactics triggering penalties. SpamBrain's ability to detect manipulative link patterns has improved with each iteration, and the 2026 version specifically addresses more sophisticated schemes that evaded prior detection.

Action Plan: Protect Your Rankings Now

Review Google's spam policies. Read the current Google spam policies documentation in full. Know exactly what constitutes a violation in 2026.
Audit your backlink profile. Use Google Search Console, Ahrefs, or Semrush to identify unnatural or suspicious inbound links. Flag anything from link farms, PBNs, or paid placements.
Disavow toxic links. For links you cannot get removed, submit a disavow file through Google Search Console. Prioritize links from known spam domains.
Check for cloaking or sneaky redirects. Verify that your server delivers identical content to Googlebot and regular users. Test with Google's URL Inspection tool.
Audit thin and duplicate content. Identify pages with minimal original value, especially any that were mass-produced. Consolidate, improve, or remove them.
Review third-party content on your domain. If you host guest posts, sponsored content, or affiliate pages, ensure they meet quality standards and are properly tagged.
Monitor Search Console for manual actions. Check the Manual Actions report daily through the end of March. If you receive one, address it immediately.
Track ranking changes. Set up daily rank tracking for your top 20-30 keywords. Document any shifts to determine if the update affected your site.
Document your E-E-A-T signals. Ensure author bios, credentials, and editorial processes are visible on your site. These signals help differentiate quality content from spam.
Prepare a recovery plan. If rankings drop, have a prioritized list of pages to audit and improve. Recovery from spam-related penalties takes 3-12 months, so speed matters.

How I Can Help

I work with businesses to audit their SEO foundations before updates like this cause damage, not after. That means reviewing your link profile, content quality, technical setup, and spam policy compliance with a focus on practical fixes. If you are seeing early signs of ranking movement from this update, or you want to get ahead of it while the rollout is still in progress, I can run a focused audit and give you a prioritized action list. Reach out here to get started, or check out my full range of services for ongoing SEO support.

Frequently Asked Questions

What is Google's March 2026 spam update targeting?

The March 2026 spam update targets spam policy violations through improvements to Google's SpamBrain AI system. Primary targets include parasite SEO, manipulative link schemes, thin AI-generated content, cloaking, expired domain abuse, and scaled content abuse. The update enforces existing spam policies rather than introducing new ones.

How long will the March 2026 spam update take to roll out?

Google estimates the rollout will complete in a few days, potentially by March 27-28. This is significantly faster than the August 2025 spam update, which took nearly four weeks. The shorter timeline suggests a more targeted and focused enforcement action.

What should I do if my rankings drop after the March 2026 spam update?

Start by reviewing Google's spam policies documentation to identify any violations. Audit your site for thin content, unnatural links, cloaking, or other policy violations. Remove or disavow problematic links, improve thin content with original value, and submit a reconsideration request if you received a manual action. Recovery from spam-related penalties typically takes 3-12 months.

Does the March 2026 spam update affect AI-generated content?

The update targets AI-generated spam specifically, not all AI-assisted content. Google's policy distinguishes between helpful AI-assisted content and scaled content abuse where AI is used to mass-produce low-quality pages designed to manipulate rankings. If your AI-assisted content provides genuine value and follows E-E-A-T principles, it should not be affected.

Is the March 2026 spam update the same as a core update?

No. Spam updates and core updates are different. Core updates change how Google evaluates content quality broadly, while spam updates specifically target pages that violate Google's spam policies. The March 2026 spam update focuses on enforcement of existing spam policies through SpamBrain improvements, not broad ranking algorithm changes.

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Originally published at mattkundodigitalmarketing.com

Sales Conversion Rates: 2026 Benchmarks and How to Improve

Matt Kundo — Tue, 24 Mar 2026 00:53:10 +0000

I spent three months auditing the sales pipeline for a client who was convinced their marketing was broken. Turns out, their lead volume was fine. Their conversion rate was 1.2%, roughly half the industry average, and nobody on the team had even measured it. That single number explained why revenue felt stagnant despite increasing ad spend every quarter.

Understanding what is a good conversion rate for sales is one of the most important things you can do for your business. It tells you whether your sales process is healthy, where deals are falling apart, and how much revenue you can realistically expect from your pipeline. Whether you are trying to figure out how to get more sales leads or just trying to close the ones you already have, the answer starts with this one metric. In this guide, I will walk you through the benchmarks that matter, the funnel math behind them, and the strategies that actually move the needle on your sales conversion rate.

1. [What Is a Sales Conversion Rate](#what-is-a-sales-conversion-rate)

2. [What Is a Good Conversion Rate for Sales? The 2026 Benchmarks](#2026-benchmarks)

3. [Understanding Your Sales Funnel: Where Deals Get Lost](#sales-funnel)

4. [How to Get More Sales Leads (and Convert the Ones You Have)](#how-to-get-more-sales-leads)

5. [Which Lead Sources Actually Convert Best](#lead-sources)

6. [5 Proven Strategies to Improve Your Sales Conversion Rate](#5-strategies)

7. [Ready to Close More Deals?](#ready-to-close-more-deals)

8. [Frequently Asked Questions](#faq)

What Is a Sales Conversion Rate (and Why It Matters More Than You Think)

Your sales conversion rate measures the percentage of leads or prospects who become paying customers. The formula is straightforward:

(Number of Closed Deals / Total Number of Leads) x 100 = Sales Conversion Rate (%)

For example, if your sales team works 200 leads in a month and closes 20 of them, your conversion rate is 10%. Simple enough. But the implications run deep.

This metric is the foundation of revenue forecasting. When you know your conversion rate, you can work backward from revenue targets to determine exactly how many leads you need. If you need $100,000 in monthly revenue and your average deal is $5,000, you need 20 closed deals. At a 10% conversion rate, that means 200 qualified leads in your pipeline.

Most businesses I work with through our Google Ads management services are surprised when they first calculate this number. Many have never tracked it at all, which means they are spending money on lead generation without knowing whether those leads are actually turning into revenue.

The distinction between website conversion rates and sales conversion rates matters here. A website conversion rate tracks visitors who take an action like filling out a form. A sales conversion rate tracks what happens after that, when a real person tries to close the deal. Both matter, but the sales conversion rate is where revenue lives.

A good conversion rate for sales also serves as an early warning system. If your rate drops month over month, something has changed: lead quality, messaging, pricing, or competitive pressure. Tracking this metric consistently lets you catch problems before they become revenue crises.

What Is a Good Conversion Rate for Sales? The 2026 Benchmarks

So what is a good conversion rate for sales in 2026? The short answer: a good conversion rate for sales typically falls between 2% and 5%, depending on your industry, sales model, and deal complexity. But that range masks enormous variation, and knowing where you fall relative to your specific peers matters far more than chasing a universal number.

Here is how to think about performance tiers:

Poor: Below 1.5% (common in luxury, high-consideration purchases)
Average: 1.8% to 3.3% for most businesses
Good: 3.5% to 5%, representing the top quarter of performers
Excellent: Above 5%, typically seen in the top 10% of companies

According to OptiMonk's 2026 benchmark data, the top 10% of performers across all industries achieve conversion rates between 3.5% and 5%. Meanwhile, First Page Sage reports the median B2B conversion rate across all industries sits at 2.9%.

Sales Conversion Rates by Industry

What constitutes a "good" rate varies dramatically by industry. Here are the current benchmarks:

    Industry
    Average Conversion Rate



  Legal Services4.3% to 9.3%
  Professional Services4.6%
  Food and Beverage4.5% to 7.1%
  Finance and Insurance3.0% to 5.1%
  Healthcare3.0% to 4.0%
  Manufacturing3.0% to 5.0%
  Beauty and Personal Care3.5% to 6.8%
  B2B SaaS and Technology1.1% to 2.9%
  E-commerce (General)1.8% to 3.3%
  Consumer Electronics1.4% to 3.6%
  Apparel and Fashion1.4% to 2.8%
  Luxury and Jewelry1.0% to 2.6%

Notice the pattern: industries with urgent needs and lower purchase consideration (legal, healthcare) convert at much higher rates than those involving complex, high-ticket decisions (SaaS, luxury). A SaaS company converting at 2.5% might be outperforming its peers, while a legal services firm at 3% could be underperforming significantly.

This is why comparing your conversion rate to a generic average is misleading. You need to benchmark against your specific industry, deal size, and sales model. The question of what is a good conversion rate for sales has a different answer for every business, and the answer depends on context.

Understanding Your Sales Funnel: Where Deals Actually Get Lost

Your overall sales conversion rate is actually the product of several stage-by-stage conversion rates stacked on top of each other. Understanding where the funnel leaks is far more actionable than just knowing the final number.

Here are the average B2B sales funnel conversion rates at each stage:

    Funnel Stage
    Average Conversion Rate



  Website Visitor to Lead2.3%
  Lead to Marketing Qualified Lead (MQL)31%
  MQL to Sales Qualified Lead (SQL)13%
  SQL to Opportunity30% to 59%
  Opportunity to Closed Deal22% to 30%

The math is sobering. For every 1,000 website visitors, roughly 23 become leads. Of those, about 7 become MQLs, and only 1 becomes an SQL. Even in the best case, you are looking at a fraction of a fraction converting to revenue.

Deal size also dramatically impacts your close rate. Smaller deals close faster and more frequently:

    Deal Size
    Average Close Rate



  Under $10,000Approximately 26%
  $10,000 to $50,00018% to 22%
  $50,000 to $500,000Approximately 15%
  Over $5 millionApproximately 9%

This is why it is critical to identify exactly where your funnel breaks down. A business with strong lead volume but low MQL-to-SQL conversion likely has a lead quality problem. One with good SQLs but poor close rates probably has a sales process or pricing issue. Diagnosing the specific stage tells you where to focus your improvement efforts.

How to Get More Sales Leads (and Convert the Ones You Have)

If you are wondering how to get more sales leads, you are asking the right question, but only half of it. Generating more leads only helps if you can actually convert them. The most effective approach is working both sides of the equation simultaneously: improving lead volume and improving the rate at which existing leads become customers. Too many businesses focus exclusively on getting more sales leads at the top of the funnel while ignoring the conversion problems further down.

Speed-to-Lead: The Hidden Conversion Killer

One of the most impactful and most overlooked factors in sales conversion is response time. The data on this is striking.

According to a Harvard Business Review study of over 2,200 U.S. companies, firms that contacted leads within one hour were seven times more likely to qualify the lead compared to those who waited even one additional hour. They were 60 times more likely to qualify than companies waiting 24 hours or more.

Research from LeanData shows that 78% of customers buy from the first company that responds to their inquiry. And responding within five minutes increases your chances of conversion by 400% compared to responding after 10 minutes.

Yet the average B2B company takes 42 hours to respond to a new lead, and 71% of leads never receive a response at all. If you are not responding to inquiries within minutes, you are leaving significant revenue on the table.

Lead Qualification Frameworks That Actually Work

Not every lead deserves the same level of attention. Using a structured qualification framework helps your team focus on the prospects most likely to convert.

BANT (Budget, Authority, Need, Timeline) works best for high-volume, transactional sales with short cycles under 30 days. It is quick to implement and requires minimal training.

CHAMP (Challenges, Authority, Money, Prioritization) starts with the buyer's pain points rather than their budget. It works well for consultative, mid-market sales where building trust matters more than rapid qualification.

MEDDIC (Metrics, Economic Buyer, Decision Criteria, Decision Process, Identify Pain, Champion) is the most comprehensive framework, designed for enterprise deals with long cycles and multiple stakeholders. Research from RevNew shows that using structured qualification frameworks can boost sales success by up to 67%.

Follow-Up Discipline

According to Martal Group's analysis, 50% of salespeople give up after a single contact attempt, and 80% give up after three touches. Meanwhile, the data consistently shows that most sales require five or more follow-up interactions to close.

If you are working with a Google Ads expert to drive paid traffic, all that spend is wasted if your sales team abandons leads after one or two attempts.

Which Lead Sources Actually Convert Best?

Where your leads come from significantly impacts how likely they are to convert. Here is what the data shows, based on research from Landbase:

    Lead Source
    Typical Conversion Rate



  Referrals2.9% to 26%
  Organic Search (SEO)2.6% to 2.7%
  Email Marketing2.4%
  Paid Search (PPC)1.5% to 3.2%
  Social Media (B2B)Below 1%

Referral leads dominate because they come with pre-built trust. Someone a prospect already knows has vouched for you, which dramatically shortens the sales cycle and reduces skepticism.

Organic search performs consistently well because these prospects are actively looking for solutions. They have self-identified a problem and are researching answers, which signals intent.

Paid search conversion rates vary widely depending on targeting quality, keyword selection, and landing page optimization. When done well, PPC can match or exceed organic search performance.

The takeaway if you want to get more sales leads that actually convert is not to pick one channel and double down. Instead, build a diversified lead generation strategy that includes referral programs, SEO content, and targeted paid campaigns. Each channel attracts prospects at different stages of the buying journey, which affects your overall conversion rate for sales. Track conversion rates by source using a tool like Google Analytics 4 so you can allocate budget to the channels that actually drive revenue.

5 Proven Strategies to Improve Your Sales Conversion Rate

Now that you understand your benchmarks, your funnel stages, and which lead sources convert best, here are the five highest-impact strategies for improving your sales conversion rate. Every one of these is backed by data, and each addresses a specific stage of how to get more sales leads through to close.

1. Respond to Every Lead Within 5 Minutes

This single change can improve your conversion rate by up to 391%, according to speed-to-lead research. Set up automated notifications, assign round-robin lead routing, and establish a response time SLA for your team.

2. Score and Qualify Every Lead Before It Hits Sales

Implement a lead scoring system that prioritizes high-intent prospects. Align marketing and sales on what constitutes an MQL versus an SQL. When frameworks like BANT or MEDDIC are applied consistently, conversion rates improve by up to 67%.

3. Align Marketing and Sales on Shared Definitions

One of the most common reasons for poor conversion rates is misalignment between marketing and sales. Marketing sends over "leads" that sales considers unqualified. Sales blames marketing for poor lead quality. Marketing blames sales for not following up. Break this cycle by agreeing on specific criteria for each funnel stage.

4. Use CRM Data to Personalize Every Interaction

According to VWO research, adding live chat alone can increase conversion rates by 40% and revenue per chat hour by 48%. Use your CRM data to personalize outreach based on industry, company size, and the specific pages a prospect visited before converting.

5. Invest in Conversion Rate Optimization

HubSpot's CRO data shows that optimizing conversion rates without increasing ad spend can reduce cost per lead by 33%. Across the industry, CRO investments deliver an average return of 223%. Even a 1% improvement in overall conversion rate can increase revenue by 30% to 50%.

Ready to Close More Deals?

Now you know what is a good conversion rate for sales, where the benchmarks sit across industries, and which strategies drive the biggest improvements. The difference between a 2% and a 4% sales conversion rate is not incremental. It is the difference between struggling to hit targets and consistently exceeding them, often with the same lead volume and the same sales team.

I help businesses build marketing systems that generate higher-quality leads and improve conversion rates across the entire funnel. From paid media campaigns that attract the right prospects to analytics setups that reveal exactly where your pipeline leaks, my approach is rooted in data and focused on measurable results.

Here is what that looks like in practice:

Paid media campaigns optimized for lead quality, not just volume
Conversion tracking that connects marketing spend to actual closed deals
Landing page and funnel optimization based on real performance data
Sales and marketing alignment consulting to eliminate pipeline friction

If your conversion rate is below your industry benchmark, or if you do not know your conversion rate at all, that is the place to start. Schedule a free consultation to discuss your sales pipeline, or explore my marketing services to see how I can help.

Frequently Asked Questions

What is a good conversion rate for sales?

A good conversion rate for sales typically ranges from 2% to 5%, depending on your industry and business model. The median across B2B industries is approximately 2.9%. Legal services and professional services tend to convert at higher rates (4% to 9%), while SaaS and luxury industries average lower (1% to 3%). Top performers in any industry typically exceed 5%. If you are below your industry average, there is significant room for improvement using the strategies covered in this guide.

How do you calculate sales conversion rate?

Divide the number of closed deals by the total number of leads, then multiply by 100. For example, if you closed 15 deals from 150 leads, your conversion rate is (15 / 150) x 100 = 10%. Make sure you are consistent about what counts as a "lead" and what counts as a "closed deal" so your data is reliable over time.

What is the average B2B sales conversion rate?

The average B2B sales conversion rate is approximately 2.9% according to 2025 benchmark data from First Page Sage. However, this varies significantly by industry. Professional services convert around 4.6%, while B2B SaaS companies average 1.1% to 2.9%. Close rates from qualified opportunities are much higher, averaging 22% to 30%.

Why is my sales conversion rate so low?

The three most common causes of a low conversion rate for sales are slow lead response time (the average B2B company takes 42 hours to respond), poor lead qualification (wasting time on unqualified prospects), and insufficient follow-up (50% of salespeople abandon leads after one contact). Start by measuring your response time and comparing your funnel stage conversion rates to the benchmarks in this article. Often, fixing just one of these issues can boost your conversion rate significantly.

How can I improve my sales conversion rate quickly?

The fastest way to improve your sales conversion rate and get more sales leads through your funnel is reducing your lead response time. Companies that respond within five minutes are 400% more likely to convert than those responding after 10 minutes. Beyond speed, implement a lead qualification framework (BANT, CHAMP, or MEDDIC) and commit to a minimum of five follow-up touches per lead. These changes alone can transform what is a good conversion rate for sales from an aspirational benchmark into your actual performance.

What is the difference between conversion rate and close rate?

Conversion rate typically refers to the percentage of all leads that become customers, measuring the entire journey from first contact to closed deal. Close rate specifically measures the percentage of qualified opportunities or proposals that result in a sale. Your close rate will always be higher than your overall conversion rate because it starts further down the funnel with already-qualified prospects.

Originally published at mattkundodigitalmarketing.com

How to Size a Home Battery: How Much Storage Do You Actually Need?

Matt Kundo — Tue, 24 Mar 2026 00:52:14 +0000

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  How to Size a Home Battery: How Much Storage Do You Actually Need?

Most Texas homes need a battery energy storage system for home backup sized at 10–15 kWh for partial backup or 20–30+ kWh for whole-home coverage including AC. Texas households average 36.5 kWh per day — 28% above the national average — with air conditioning consuming 50–70% of summer electricity. A single 13.5 kWh battery handles essentials plus limited AC, while two units provide full whole-home protection.

Choosing the right battery energy storage system for home use starts with one question: how much power do you actually need? Texas homes use about 28% more electricity than the national average — and a battery that works in Michigan may fall short during a July heat wave in Dallas. Here's how to figure out the right home battery storage capacity for your household.

How Much Energy Does Your Home Actually Use?

The average U.S. household uses about 28.4 kWh per day, according to the EIA. But Texas homes average 36.5 kWh per day — roughly 1,096 kWh per month, according to Choose Texas Power.

In summer, that number climbs to 40–50 kWh per day. Air conditioning accounts for 50–70% of summer electricity use in Texas, according to Strickland HVAC. A 3-ton central AC unit alone draws 2,500–3,500 watts per hour.

Start by checking your electricity bill for your average monthly kWh, then divide by 30. That daily number is your baseline for sizing a battery energy storage system for home backup.

How to Calculate the Right Battery Size

Figuring out how much battery storage do I need for my home comes down to three decisions:

Step 1: Decide what to back up. Essential circuits only (fridge, lights, Wi-Fi)? Partial home? Or everything including AC?

Step 2: Choose your backup duration. Most homeowners target 12–24 hours for essential loads.

Step 3: Use the simplified formula.

Required Battery Capacity = Daily kWh Need ÷ (Depth of Discharge × Efficiency)

Modern lithium batteries offer 90–100% depth of discharge and 90–97% round-trip efficiency, according to Anern. Here are the three home battery storage capacity tiers:

Essential backup (5–10 kWh): Fridge, lights, Wi-Fi, phone chargers — lasts 10–24 hours
Partial home (10–15 kWh): Essentials plus fans, TV, select outlets — or essentials with AC for 4–6 hours
Whole home (20–30+ kWh): Everything including central AC — typically requires two battery units

What Can Different Battery Sizes Power?

Understanding home battery storage capacity at each tier helps you choose the right system:

Battery Size
What It Powers
Duration

10 kWh
Fridge, lights, Wi-Fi, chargers
10–24 hours

15 kWh
Essentials + AC (4–6 hrs) or essentials only (24+ hrs)
4–24+ hours

20+ kWh
Whole home with AC
8–12 hours

A 10kw home battery storage setup handles essentials well, but won't keep your AC running long. A 3-ton AC unit uses 20–28 kWh over 8 hours — that single appliance can drain a 10 kWh battery in about 3 hours.

NREL recommends sizing batteries to support at least 1.5 times the expected peak load for reliability.

Top Home Batteries for Texas Homeowners

Here's how the leading battery energy storage systems for home use compare:

Battery
Capacity
Continuous Power
Warranty

Tesla Powerwall 3
13.5 kWh
11.5 kW
10 years

FranklinWH aPower 2
15 kWh
10 kW
15 years

Enphase IQ 5P
5 kWh (modular)
3.84 kW/unit
15 years

The Powerwall 3 hits a sweet spot for most Texas homes — 13.5 kWh provides solid partial-home backup with enough power output (11.5 kW) to start and run central AC. For larger homes, the FranklinWH offers 15 kWh with a longer warranty. The Enphase system is ideal if you want to start small and scale up.

For detailed pricing, see our cost of battery storage per kWh guide.

Why Battery Sizing Is Different in Texas

Texas homeowners face unique home battery storage capacity challenges. Central AC is the biggest factor — running a 3-ton unit for 8 hours uses 20–28 kWh, which is why whole-home backup typically requires 20+ kWh.

ERCOT peak demand could rise from 85,000 MW to 145,000 MW within five years, according to Ascend Analytics. That means more conservation appeals and potential brownouts.

With Ambit Energy's Free Nights plans, you can charge your battery for $0 overnight and discharge during expensive daytime hours — turning your battery energy storage system for home use into a daily bill-reduction tool, not just emergency backup.

At Ambit Energy VIP Energy Service, we help Texas homeowners find the right battery storage installation and energy plan combination for their needs.

Ready to Size Your Home Battery?

Get a free energy quote and find the right battery + plan combination.

Get Your Free Quote

Enroll Online

Frequently Asked Questions

How much battery storage do I need for my home?

Most Texas homes need 10–15 kWh for partial backup (essentials plus limited AC) or 20–30+ kWh for whole-home backup including air conditioning. Start by checking your daily kWh usage on your electricity bill and deciding which circuits you want to protect.

Can a home battery run my air conditioner?

Yes, but AC is the largest residential load. A 3-ton central AC unit draws 2,500–3,500 watts, using 20–28 kWh over 8 hours. You need at least 13.5 kWh (like a Tesla Powerwall 3) for 4–6 hours of AC runtime, or 27+ kWh for extended cooling.

Is 10 kWh enough for a Texas home?

A 10kw home battery storage system can power essential loads (refrigerator, lights, Wi-Fi, phone chargers) for 10–24 hours. However, it won't sustain air conditioning for long. For Texas summers, 13.5–15 kWh is a more practical starting point.

Sources

Originally published at vipenergyservice.com

DEV Community: Matt Kundo

Meta Adaptive Ranking Model: What Instagram Advertisers Gain in 2026 | MKDM

Meta's Adaptive Ranking Model Gives Instagram Ads a Measurable Boost in 2026

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Do I need to change my Instagram ad settings to benefit from this update?

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