CMOs: 2026 BlackRock Outlook Demands Digital Ad Shifts

BlackRock’s latest market commentary says what we’re all feeling: persistent inflation and weird consumer spending shifts mean a complicated economic outlook for CMOs going into 2026. To adapt, our marketing strategies have to get way more precise with targeting and campaign management. So, how do we actually translate these big, scary macro-economic shifts into specific, actionable changes in our digital ad accounts?

Setting Up Economic Sensitivity Filters in Google Ads Manager

You have to figure out which consumer segments are getting squeezed by the economy. The 2026 version of Google Ads Manager has some seriously useful new filters that help you find and target audiences based on their economic resilience. It’s about behavioral patterns that signal financial strain or stability, not just old-school demographics.

Step 1: Accessing Audience Insights

First, log into your Google Ads account. On the left menu, find and click Tools and Settings, then under the “Planning” column, pick Audience Manager. This is your command center for seeing all your existing audience segments, including your own custom ones and the segments Google gives you.

Step 2: Applying the Economic Sensitivity Score Filter

Once you’re in Audience Manager, go to the Audience Segments tab. You’ll see a list of your audience data. To get to the new filter, click the + New Segment button and choose Custom Segment. In the “Segment Type” dropdown, you’re looking for Economic Sensitivity Score. This gives you a slider from 1 (Highly Sensitive) to 10 (Highly Resilient). If you’re running a campaign for people likely feeling inflation’s pinch, you’ll want to set that slider to include scores from 1 to 5. On the flip side, if you’re selling a luxury product to a more recession-proof crowd, focus on scores 7 to 10. I find that starting with a range of 3 to 6 is a good middle ground for testing new messaging.

Pro Tip: Combining Filters

Don’t just use the one filter and call it a day. You get real power when you combine the Economic Sensitivity Score with other behavioral or demographic filters. For example, try pairing a “Highly Sensitive” score (1-3) with an “Interest in Budget Travel” to find a super price-conscious segment. A late 2025 eMarketer report already confirmed consumers are scrambling for value, and ad spend is following the platforms that can prove their ROI.

Common Mistake: Over-Filtering

A classic mistake is getting too specific and applying so many filters that your audience is too small to be useful. You should be aiming for a target audience of at least 500,000 unique users for any broad campaign, otherwise you won’t have enough reach or data to optimize properly. Always keep an eye on the estimated reach number that Google Ads Manager shows you as you apply filters.

Expected Outcome

When you segment audiences based on their economic sensitivity, you can write ad copy and create offers that actually speak to them. You should expect to see your click-through rates (CTR) and conversion rates (CVR) climb for these campaigns because the messaging will land much better with people’s current financial situations.

Adjusting Bidding Strategies in Meta Ads Manager for Value Optimization

Meta’s ad platform is always changing, and the 2026 version has sophisticated tools for optimizing spend that are especially important when money’s tight. The conversation has shifted from just getting conversions to getting conversions that bring in real money.

Step 1: Working through to Campaign Settings

Pop open your Meta Ads Manager and pick the campaign you need to tweak. If you’re starting fresh, pick an objective like Sales or Leads. Once you’re in the campaign, click down to the Ad Set level, which is where almost all the important bidding and optimization settings live.

Step 2: Selecting Value Optimization

Scroll down until you find the Optimization & Delivery section. Under “Optimization for Ad Delivery,” you’ll see the usual suspects: “Conversions,” “Link Clicks,” “Landing Page Views.” For any e-commerce business, or really any business where one sale can be worth more than another, you want to select Value Optimization. This tells Meta’s algorithm to stop chasing just anyone who might convert and instead find people who are likely to make bigger purchases or become more valuable customers.

Pro Tip: Integrating with Your CRM

If you really want to make Value Optimization sing, you have to make sure your Meta Pixel is set up right to pass purchase values back to Meta. Even better, integrate your CRM data through Meta’s Conversions API. This gives Meta a sense of the lifetime value (LTV) of your customers, which makes its targeting for high-value prospects insanely precise. I’ve seen clients get a 10-15% bump in average order value (AOV) within just a few months of getting this fully wired up.

Common Mistake: Insufficient Data

Value Optimization needs data to work, specifically historical purchase value data. If your pixel hasn’t seen enough action (the general rule of thumb is less than 50 valued conversions a week), Meta’s algorithm is just guessing and won’t be effective. If that’s you, start with the standard “Conversions” optimization and then flip the switch to “Value Optimization” once you’ve built up enough data. A Nielsen report from Q4 2025 basically said that without strong first-party data, your AI ad tools are flying blind.

Expected Outcome

By making the switch to Value Optimization, you’ll start to see the average value of your conversions go up, not just the total number of them. This directly boosts your return on ad spend (ROAS), which is the metric that matters most when every dollar in your marketing budget is being scrutinized.

Using Adobe Analytics for Churn Prediction and Re-engagement

When the economy is rocky, you can’t afford to lose the customers you already have. The 2026 Adobe Analytics suite has some advanced predictive features that can flag customers who are about to churn, letting you step in before it’s too late.

Step 1: Accessing the Predictive Analytics Workspace

Log in to your Adobe Analytics account. From your main dashboard, go to Workspace in the left panel. Either open an existing workspace or create a new one. Find the Predictive Analytics tab, which is usually tucked under the “Components” section in the left rail.

Step 2: Configuring the Churn Prediction Module

Inside the Predictive Analytics tab, find the Churn Prediction module and drag it onto your workspace. The tool will then make you define what “churn” actually means for your business (is it no purchases in 90 days? no logins in 60 days?). You’ll select the data sets it should look at, like “Customer ID” and “Purchase History.” The module then chews through your historical data to build a model that spots the patterns that usually show up right before a customer disappears.

Pro Tip: Dynamic Segmentation

After the model spits out a list of at-risk customers, don’t just sit on it. Create a dynamic segment in Adobe Analytics for this “High Churn Risk” audience. You can then export that segment and upload it straight into your email platform (like HubSpot Marketing Hub) or your ad platforms (Google Ads, Meta Ads) as a custom audience. This lets you run highly targeted re-engagement campaigns with a special offer or loyalty bonus to win them back. HubSpot’s own research from early 2026 showed that boosting retention by just 5% can jack up profits by 25% to 95%.

Common Mistake: Ignoring the “Why”

It’s great to know *who* is about to churn, but it’s not enough. You have to figure out *why*. While the Churn Prediction module gives you the “who,” you should use other tools in Adobe Analytics like “Flow Analysis” or “Fallout Reports” to see the user journeys that lead to churn. Are people bailing at a specific page in your checkout? Is there a feature nobody’s using? Fixing the root of the problem is way more effective than just throwing discount codes at people.

Expected Outcome

By finding and re-engaging these at-risk customers before they’re gone, you can make a real dent in your churn rate. This has a direct impact on your customer lifetime value (CLTV) and creates a more stable revenue base, which is a lifesaver when the cost of acquiring new customers is climbing. You should see your retention campaigns get a 5-7% lift in reactivated customers if you do this right.

Refining Audience Exclusion Lists Across Platforms

In a tight economy, you can’t afford to waste a single ad impression. One of the simplest ways to get more efficient is to stop showing ads to people who are never going to buy from you. This is what exclusion lists are for.

Step 1: Identifying Irrelevant Segments

Go through your performance data on Google Ads, Meta Ads, and your other platforms. Look for audience segments that have consistently low engagement, high bounce rates, or zero conversions, and pay extra attention if they are also flagged as “Highly Sensitive” by Google’s new score. Think about segments who might be interested in what you sell but just can’t afford it right now. If you’re selling luxury watches, it’s time to exclude lower-income zip codes or interest groups related to budgeting.

Step 2: Implementing Exclusions in Google Ads

In Google Ads Manager, go to Audiences on the left menu, then click the Exclusions tab. From here you can add a few types of exclusions:

1. Audience Segments: Click the blue + Add Audience Exclusions button. Choose whether to apply it at the “Campaign” or “Ad Group” level, then find the segments you want to block. This is where you’d add that “Highly Sensitive” segment you found earlier.
2. Demographics: Under the “Demographics” menu on the left, you can cut out entire age ranges, genders, or parental statuses if the data shows they never convert.
3. Geographic Locations: Go to Locations on the left menu, then to the Excluded tab. Here you can add specific cities, states, or even zip codes where your product doesn’t sell or where economic data suggests people aren’t spending.

Step 3: Implementing Exclusions in Meta Ads

In Meta Ads Manager, this is done at the Ad Set level. In the “Audience” section, there’s an option to Exclude people.

1. Custom Audiences: This is where you upload lists of people you don’t want to target. Think customers who just churned, people who opted out of your emails, or that high-risk segment you identified with your Adobe Analytics churn model.
2. Detailed Targeting Exclusions: You can also exclude people based on their interests, behaviors, or demographics. For example, if you’re trying to reach high-net-worth individuals, you could exclude interests like “discount shopping” or “coupon codes.”

Pro Tip: Automated Exclusion Rules

If you’re running a lot of campaigns, managing this manually is a pain. Set up automated rules. In Google Ads, you can go to Tools and Settings > Rules and create a rule that automatically excludes a placement or an audience if it hits certain criteria (for example, if it gets 1,000 impressions and 0 conversions while spending over $50). This automates your spring cleaning.

Common Mistake: Blanket Exclusions

Be careful not to get too aggressive here. Making huge, sweeping exclusions can backfire and cut off potentially valuable pockets of customers. It’s always better to test your exclusions on a smaller scale first and watch what happens to your reach and performance. A slow and steady approach of trimming out the worst-performing segments is usually safer than taking a giant axe to your targeting.

Expected Outcome

By keeping your exclusion lists clean and updated, you’ll immediately cut down on wasted ad spend and see your overall campaign efficiency go up. Your budget starts working harder by reaching more people who might actually buy something, which in the end leads to a much healthier ROAS. A well-managed exclusion list should be able to lower your cost-per-acquisition (CPA) by 5-10%.

This 2026 economic field is going to be tricky, no doubt. But it demands a smarter, data-first approach to marketing. If you get really precise with your targeting, optimize for actual business value, get ahead of customer churn, and diligently cut out waste, you can make your strategies resilient. You can turn these economic headwinds into an opportunity to get more efficient and pull ahead of the competition.