Email performance depends on your audience, not just your content. You already know this. You've tested subject lines, adjusted send times, and refined your copy. But you're still guessing which donor segments will give, which volunteers will show up, which constituents will enroll, or which B2B prospects will convert.
HubSpot removed the guesswork
(as of Feb 2, 2026 - Predicted Email Engagement in Segments is now in Public Beta).
Their new Predicted Email Engagement feature analyzes historical engagement patterns within your contact segments and tells you (before you hit send) whether a segment will perform above average, average, or below average. Available across all HubSpot hubs and tiers, this isn't a premium feature locked behind enterprise pricing. This is baseline functionality now.
This changes how you allocate resources. Instead of building manual reports or relying on intuition about which audiences to prioritize, you get data-backed predictions to focus efforts on high-potential segments. Whether you're driving donations, program enrollment, or B2B sales, the time savings compound. The accuracy improves. The results follow.
AI is integrating into marketing workflows in a consistent way: predictive analytics removes the send-and-see approach dominating email marketing for years.
What used to require manual analysis (pulling engagement data, comparing segments, identifying patterns) now happens automatically. HubSpot's system compares each segment's historical engagement against the average engagement of all contacts in your instance. You get a classification: High, Medium, Low, or Unknown.
The Unknown classification appears when there's insufficient data for prediction. Honest. Useful. You know where you need more information.
The data here is substantial. According to research on AI-powered personalization, organizations using these tools see a 41% increase in revenue and a 13.44% boost in click-through rates. In 2026, marketers using AI email optimization report 38% higher open rates, 45% better click-through rates, and 52% more conversions. For nonprofits, this translates to more donations per campaign. For government agencies, higher enrollment rates. For B2B, shorter sales cycles.
These aren't marginal improvements. These are performance gaps creating a real separation between organizations that are maximizing their outreach and those that are falling behind.
The implementation is straightforward, which matters when you're evaluating whether a tool will get used or sit ignored in your tech stack.
You create or navigate to a contact segment. The predicted email engagement data appears in two places: the Overview section and the Performance tab under Available Channels.
The system analyzes past engagement. This looks at how contacts in your segment have interacted with previous emails (opens, clicks, conversions) and compares their behavior to the average across your overall contact database.
You get a clear classification. High means above-average expected engagement. Medium means average. Low means below-average. Unknown means the system needs more data.
The value comes from what you do with this information. Your organization has options:
Prioritize high-engagement segments for time-sensitive campaigns (fundraising deadlines, program enrollment windows, product launches)
Adjust messaging strategy for medium-engagement segments (cultivation emails for donors, awareness campaigns for constituents, nurture sequences for prospects)
Reconsider whether low-engagement segments are worth the send, or if they need re-engagement campaigns first
Identify Unknown segments where you need to gather more engagement data before making strategic decisions
This changes resource allocation. You're no longer spreading effort evenly across all segments, hoping something will work. You're making informed decisions about where to allocate your time to generate the highest return.
HubSpot's feature sits inside a larger transformation happening across marketing operations. According to Litmus research, 41% of companies will use AI-driven analytics by the end of 2026, and marketers estimate 75% of their email operations will be AI-powered by then.
This timeline is immediate. Not future-state planning. Current operational reality.
The pressure is real across sectors. Research shows 76% of marketers agree organizations failing to adopt AI in their communication strategies will face a disadvantage. When three-quarters of your peers agree on a trend, the trend has arrived. Nonprofits compete for donor attention. Government agencies compete for constituent engagement. B2B companies compete for pipeline.
The shift from reactive to proactive marketing creates operational advantages that compound over time. Instead of analyzing campaign performance after the fact and adjusting for the next send, you're making strategic decisions before the campaign launches. You're optimizing in real time rather than in retrospect.
Email list segmentation remains one of the most effective tactics in email communications. According to multiple industry studies, segmented email campaigns drive 30% more opens and 50% more click-throughs than non-segmented ones. But segmentation only works when you know which segments will perform. Whether you're segmenting major donors from first-time givers, active volunteers from interested prospects, or enrolled citizens from eligible non-participants, HubSpot's AI makes segmentation smarter by adding predictive capability to what was previously educated guesswork.
The efficiency gains break down into three categories: time to launch, time to engagement, and targeting accuracy.
Time to launch decreases because you're not building custom reports to analyze segment performance. The prediction is already there when you open the segment. You move from analysis to decision faster.
Time-to-engagement improves because you're sending to segments predicted to engage. No waiting to see if a segment responds. You've identified high-probability audiences before the send.
Targeting accuracy increases because the system analyzes patterns across your entire contact database. This identifies engagement behaviors you might miss in manual analysis. The machine learning model finds correlations not immediately obvious to human pattern recognition.
These improvements stack. Faster launch times mean you test more variations. Better engagement means your sender reputation improves, which affects deliverability. Higher accuracy means your team focuses energy on segments that drive results (donations, enrollments, conversions) rather than on segments that ignore your outreach.
Need help implementing AI-driven email strategies in your HubSpot instance? Talk to us about optimizing your email performance.
The practical application depends on your current email operations maturity, but the variables are clearly defined.
If you're running basic email campaigns without sophisticated segmentation, this feature gives you immediate insight into which segments deserve more attention. You can start prioritizing high-engagement audiences without building a complex reporting infrastructure.
Already doing advanced segmentation? This adds predictive capability to your existing strategy. No replacement of your segmentation logic. You're adding a layer of intelligence, helping you prioritize which segments to activate first.
Working with limited resources? (Most teams are.) This helps you allocate time more effectively. You're not spreading effort equally across all possible segments. You're concentrating resources where they generate measurable results.
For Nonprofits: Predicted engagement helps identify which donor segments are most likely to respond to specific appeals. Major gift officers spend time cultivating high-engagement donors. Year-end campaigns target segments showing strong giving signals. Volunteer coordinators focus recruitment efforts on contacts predicted to convert from interest to action. The prediction helps small development teams punch above their weight.
For Government Agencies: Enrollment campaigns hit the right audiences at the right time. Benefits programs reach eligible citizens most likely to enroll. Public health initiatives target segments showing engagement with health communications. Community programs connect with residents, demonstrating participation patterns. Limited communications budgets go further when focused on responsive segments.
For B2B Companies: Sales and marketing alignment improves when both teams see which segments show buying signals. Product launches reach decision-makers, showing interest patterns. Demo requests go to contacts predicted to engage. Renewal campaigns target accounts showing engagement behaviors. Pipeline velocity increases when outreach focuses on responsive prospects.
The feature works across all HubSpot hubs and tiers, which means the barrier to entry is your existing HubSpot subscription. You're not evaluating whether to purchase additional tools. You're deciding whether to activate functionality you already have access to.
Predictive engagement doesn't eliminate the need for good email fundamentals. You still need clear value propositions, relevant content, and respect for subscriber preferences. List hygiene still matters.
What changes is how you deploy these fundamentals. Instead of applying the same approach to every segment, you adjust strategy based on predicted engagement levels.
High-engagement segments might receive your most ambitious campaigns: major gift asks, critical program enrollment deadlines, product launches, and signature event invitations. These audiences have demonstrated consistent engagement patterns. They're primed for action.
Medium-engagement segments might receive more educational content designed to build trust and increase engagement over time. Impact stories for donors, program benefits for constituents, thought leadership for prospects. No expectation of immediate conversion. You're playing a longer game with these contacts.
Low-engagement segments might trigger re-engagement campaigns before you include them in regular sends. Lapsed donor campaigns, inactive volunteer outreach, dormant lead sequences. Address the engagement problem directly rather than hoping repetition solves anything.
The prediction gives you strategic options. How you execute those options still depends on your organizational context, audience characteristics, and campaign objectives. A nonprofit cultivating major donors operates differently from a government agency driving benefit enrollment, which operates differently from a B2B company closing enterprise deals. The prediction works for all three.
Want to audit your current email segmentation strategy? Get a free consultation on maximizing your HubSpot email engagement.
HubSpot enables a shift from post-campaign analysis to pre-campaign optimization. You're making strategic decisions with data rather than making strategic decisions and hoping the data validates them later.
This changes planning cycles. You evaluate segment performance before committing resources to campaign creation. You test messaging variations on high-engagement segments first, then roll successful approaches to medium-engagement audiences.
The feedback loop tightens. You're learning faster because you're making informed decisions earlier in the process. The compound effect of consistently better decisions over time creates measurable performance gaps between teams using predictive tools and those relying on traditional methods.
Start with your highest-value campaigns. Year-end giving appeals. Open enrollment periods. Pipeline-critical product demos. Check predicted engagement for your target segments. If predictions show low engagement, you have options: adjust the segment criteria, modify your messaging strategy, or reconsider the campaign timing. You're making these decisions before investing time in campaign creation and execution.
Track how predictions correlate with actual performance over time. The system learns from your specific audience behaviors. The more you use it, the more accurate the predictions become for your particular contact database.
Build predicted engagement into your campaign planning process. Make this a standard checkpoint before finalizing send lists. The tool only generates value when influencing decisions. Check the prediction, adjust your approach accordingly, measure the results, and refine your strategy.
Teams that integrate AI-powered predictions into their workflows see measurable improvements in efficiency and performance. Teams treating this as optional or ignoring the feature entirely fall behind competitors who optimize using data-backed insights.
You already have access to this functionality. Will you use this to make better decisions before you hit send?
Tapp Network specializes in helping nonprofits, government agencies, and B2B companies extract maximum value from their HubSpot investment. We work with development teams, communications directors, and marketing leaders to implement AI-powered optimization strategies that drive measurable results. Whether you're increasing donor retention, boosting program enrollment, or shortening sales cycles, we deliver setup and strategic execution that compound over time. Ready to move from guessing to knowing which segments will perform? Build a data-backed email strategy with us.
Kyle Barkins co-founded Tapp Network with more than 10 years in marketing and application development, and calls on his experience to enhance the usability of web and mobile applications for high-conversions for our clients.
