A newsletter for modern marketers.
TRUSTED BY THE WORLD'S SMARTEST MARKETERS
Free ad performance benchmarks every week.
Live webinars and strategy sessions with industry leaders.
Watch all previous episodes on our YouTube channel.
Insider strategies from the smartest brands in ecommerce.
SEE LATEST POSTS:
Which Campaigns Benefit Most from C+DV? Prospecting, Reach/Traffic, and Retention by the Numbers
Which campaigns benefit most from C+DV? Prospecting, reach/traffic, and retention by the numbers
On view‑heavy platforms, people often discover you in feed or video and return later via search or direct to purchase.
Clicks-Only records a multi-touch lens, but doesn't account for the entire attribution process.
‍C+DV (Clicks + Deterministic Views) closes that gap by ingesting verified impression events from participating platforms and matching them one‑to‑one with orders alongside your first‑party click data.
That’s deterministic (factual), not probabilistic modeling, which allows views to share credit with clicks without guesswork.
This article serves as a part companion piece to a webinar I hosted about C+DV. You can see the full recording of the webinar here:
Three Objectives, Three patterns: Who Benefits Most
When you compare Clicks‑Only vs C+DV and cut results by objective, three consistent patterns emerge.
1) Prospecting (top‑of‑funnel) Prospecting campaigns usually gain meaningfully under C+DV. They’re the programs designed to generate discovery, so their impact shows up once verified views can carry their share of credit. Expect many “borderline” prospecting lines (under clicks‑only) to cross into positive territory when you widen the lens to include deterministic views and longer windows.
What to look for:
- Campaigns that miss goal on Clicks‑Only, but meet or exceed goal under C+DV—especially when their LTV/longer‑window ROAS strengthens.
- First‑time customer contribution: it’s a better read on incrementality for view‑attributable impact.
2) Reach/Traffic “Reach” and “traffic” objectives are the classic under‑credited lines in a click‑centric workflow. Under C+DV, they frequently move from ambiguous to plainly accretive because the model now attributes part of the outcome to verified exposures that didn’t earn an immediate click.
What to look for:
- A sharp contrast between Clicks‑Only and C+DV performance for reach/traffic campaigns, with bigger gains as you extend the attribution window (7/14/30‑day).
- Stronger lifts on video‑heavy placements versus static‑heavy ones, consistent with how views influence later conversion behavior.
3) Retention can benefit too, but more modestly: it’s typically a mix of genuine influence and exposures to already‑engaged customers. Treat it as a balancing lever, not your primary growth engine. When evaluating retention lift, weight first‑time vs returning customer performance differently to separate incrementality from “already going to buy.”
Why These Gains are Real (and Not “View Inflation”)
C+DV’s credit rules are deliberately conservative: rapid view‑plus‑click pairs within 30 seconds are de‑duplicated (the click wins), clicks retain even weighting, and views are pooled by platform and down‑weighted as the number of views from the same platform rises—preventing “view flooding” from stealing outsized credit. Position in the funnel doesn’t bias the view; it’s the platform‑specific pool size that matters.
What Gives Up Credit, and How to Plan Around It
As top‑of‑funnel gains credit, something else gives. You’ll often see “unattributed” shrink as view‑driven touchpoints fill clickless gaps. You’ll also see last‑click “credit catchers” (most commonly branded search and shopping) cede some conversions they previously absorbed in a Clicks‑Only world. That’s expected and healthy: the model is reallocating to the touchpoints that actually created demand across publishers.
Budget implication: protect and fund prospecting and reach/traffic programs that strengthen under C+DV; trim the bottom‑heavy skew that depended on last‑click over‑attribution.
How to Find Your Objective‑level Winners In Minutes
Here’s a quick workflow you can run every week to identify which campaigns to protect or scale.
Start broad, then narrow
Open the Model Comparison view and flip from Clicks‑Only to C+DV to see directional changes by source. Then, pivot by objective to pinpoint where lift concentrates (prospecting, reach/traffic, retention). This tells you what deserves protection before you dive into line items.
See this clip from the webinar, where I examine the model comparison:
Compare intra‑channel at the campaign level
Within each platform, compare each campaign under Clicks‑Only vs C+DV. Highlight any lines that are weak on clicks but meet/exceed goal under C+DV—especially where LTV/longer‑window performance climbs too. Those are “don’t cut—fund” candidates.
Examining how you can compare different models across channels:
Respect conversion lag on view‑heavy channels
On TikTok in particular, one‑day performance rarely tells the story; it’s common to see large jumps from 1‑day to 14/30‑day under C+DV as view influence materializes. Make 7/14/30‑day comparisons before deciding to scale, hold, or pause.
Triage for Incrementality
When judging prospecting/reach lift, emphasize first‑time customer results; you’ll get a truer read on which upper‑funnel efforts are adding net‑new value.
Concrete Examples (to Anchor the Objective Patterns)
- Reach/traffic and prospecting on Pinterest: Omnilux saw a 659% ROAS lift, 728% more transactions, and 671% more revenue on Pinterest when deterministic views were credited versus Clicks‑Only—exactly what you’d expect when awareness objectives get their due. (read the Omnilux case study here)
- Prospecting at scale on Meta: Across TubeScience brands, enabling C+DV surfaced view‑driven contribution that clicks‑only missed, with ROAS and revenue rising—e.g., Kitsch +18–25% ROAS lift and +21% revenue lift; Blissy’s blended Meta ROAS improved from 0.82 to 0.92, adding roughly $80K in attributable revenue over the analysis window. These gains align with high‑impression prospecting mixes.
Understanding how C+DVÂ influences credit in across platforms:
Guardrails (So Teams Don’t Misread Objective‑level Lift)
- Don’t compare to Clicks + Modeled Views (CMV); it’s probabilistic and includes different credit logic. Use Clicks‑Only as your baseline when assessing objective‑level lift under C+DV.
- Expect a “bake‑in” period as C+DV accrues. For objective‑level decisions (especially on Meta/TikTok), rely more on 7/14/30‑day windows and, for early weeks, assess intra‑channel decisions rather than cross‑channel budget shifts.
- When evaluating retention lift, segment by first‑time vs returning to avoid over‑reading exposures to existing customers.
Protect Discovery, Scale What Compounds
Prospecting and reach/traffic campaigns are the primary beneficiaries of C+DV because the model finally recognizes verified, cross‑publisher view influence alongside clicks.
Treat the objective‑level lift you see as a map for budget: protect the discovery lines that get stronger under C+DV (and over longer windows), rebalance away from last‑click catchers, and use first‑time customer performance as your north star for incrementality.
That’s how you fund demand creation—not just demand capture—and build a healthier, compounding mix.
To watch the full webinar, click here. Additionally, you can download our guide that explains all you need to know about Clicks +Â Deterministic Views, written by my colleague, CJÂ Hunter, and me. Download it for free here.
Fogg Behavior Model: Motivation, Ability, and Prompts
The Fogg Behavior Model (FBM) is a simple yet powerful framework for understanding why people take action, or don’t.Â
The model breaks behavior down into three elements: Motivation, Ability, and Prompt. For a behavior to occur, all three must align at the same moment.
By mapping where customers fall on the motivation-ability spectrum, and pairing that insight with the right prompt, teams can design experiences that feel intuitive, engaging, and effective, without relying on guesswork or manipulation.
In this guide, we’ll unpack how the Fogg Behavior Model works, explore the three core elements that drive behavior, and show how to apply the framework across real-world marketing and product scenarios.Â
You’ll learn how to identify behavioral bottlenecks, optimize prompts, and ethically design for action, complete with a step-by-step guide and practical examples.
Fogg Behavior Model (FBM): Origins & Core Concept
The Fogg Behavior Model (B = MAP) was developed by Dr. BJ Fogg, a researcher and founder of Stanford University’s Behavior Design Lab.Â
His work explores why people do or don’t take action, and how small shifts in design can lead to big changes in behavior.
At its core, the model states that Behavior happens when three elements converge at the same moment: Motivation, Ability, and a Prompt.Â
If any one of these is missing or too weak, the behavior won’t occur.Â
‍Fogg summarizes this as: B = MAP (Behavior = Motivation × Ability × Prompt)
In other words, even a highly motivated person won’t act if the task feels too difficult, and even the simplest task won’t happen if there’s no motivation or cue to trigger it.
To visualize this relationship, Fogg uses an “action line” plotted on a two-axis chart: Motivation on the vertical axis, Ability on the horizontal.Â
When a Prompt appears, behaviors that fall above the line are likely to happen; those below the line generally won’t.Â
This curve shows the dynamic trade-off between motivation and ability: the easier a behavior is, the less motivation it requires, and vice versa.
‍In marketing, this framework provides a powerful lens for understanding why users click, convert, or abandon a process.Â
Marketers can use it to craft more effective calls to action (the prompt), reduce friction in the customer journey (increasing ability), or boost emotional resonance and urgency (increasing motivation).Â
Whether it’s optimizing a signup flow, designing re-engagement emails, or nudging a free user toward upgrade, the Fogg Behavior Model (FBM) helps teams identify which lever to pull, and when, to drive meaningful action.
Deep Dive: Motivation, Ability & Prompts
Understanding how motivation, ability, and prompts influence behavior helps explain why some marketing campaigns convert instantly while others struggle to move the needle.Â
Each element can be adjusted, like turning a dial, to make the desired behavior more likely.
Motivation
Motivation is the “why” behind behavior; the emotional drive that moves people to act.
According to BJ Fogg, motivation is powered by three core forces:
- Sensation (pleasure or pain)
- Anticipation (hope or fear)
- Belonging (social acceptance or rejection)
These motivators operate on a spectrum from low to high. When motivation is strong, people are more willing to overcome friction; when it’s weak, even the simplest task can feel like too much effort.Â
Crucially, motivation and ability can trade off: if one is low, the other must rise for the behavior to occur.
In practice:
- Sensation might mean creating an experience that feels rewarding, like a dopamine hit from completing a challenge or receiving instant feedback.
- Anticipation plays on future benefit or loss: “Sign up today before your trial ends.”
- Belonging taps into social proof: “Join 50,000 people already using our product.”
‍Effective behavior design recognizes which motivator is most relevant for the user and activates it at the right moment.
Ability
If motivation is about wanting to act, ability is about being able to.Â
Fogg defines ability as simplicity: how easy or frictionless it is to perform the desired action.
He outlines six factors that determine simplicity:
- Time: How long the action takes.
- Money: What it costs to complete.
- Physical effort: The level of exertion required.
- Mental effort: The cognitive load or complexity involved.
- Social deviance: How much the action conflicts with social norms.
- Non-routine: Whether the behavior is unfamiliar or disruptive.
Increasing ability doesn’t necessarily mean teaching users more. It often means removing friction.Â
That could mean shortening a form, reducing choices, offering autofill options, or breaking a complex process into smaller steps.
‍In marketing, simplification is one of the fastest levers to pull: make the path to conversion, signup, or engagement effortless, and users need far less motivation to follow through.
Prompts
A Prompt (previously called a trigger) is the cue that tells someone to take action. It’s the “do this now” moment.Â
Even if motivation and ability are both high, nothing happens without a prompt.
‍Fogg identifies three main types of prompts:
- Facilitator: Used when motivation is high but ability is low. The goal is to make it easier (e.g., “Start with one click” or “We’ll walk you through it”).
- Spark: Used when ability is high but motivation is low. The goal is to inspire action (e.g., a message emphasizing urgency or benefit).
- Signal: Used when both motivation and ability are high. It’s a simple reminder (“Time to check in” or “Your order is ready”).
Timing and context are everything. A poorly timed prompt, like a push notification during a meeting or an irrelevant ad, won’t work, even if the user is otherwise ready to act.
In digital experiences, prompts often work best in chains: a small prompt leads to a small action, which unlocks another prompt, and so on.Â
Think of how a “You’ve got new likes” email brings a user back to an app, where new features or notifications encourage deeper engagement.Â
Over time, these micro-prompts build sustained habits and long-term retention.
‍Motivation, ability, and prompts rarely operate in isolation.Â
The real power of the FBMl comes from understanding their interplay: knowing when to boost desire, when to lower friction, and when to deliver the right cue.Â
Once you can map where your users fall on that spectrum, you can design experiences that feel intuitive rather than forced.
Applying the Fogg Model: Strategy & Use Cases
The Fogg Behavior Model isn’t just a way to understand human behavior, it’s a tool for improving it.Â
Once you know how motivation, ability, and prompts interact, you can start using that insight to design smarter marketing campaigns, product experiences, and user journeys.
Strategy
A practical way to use the model is to map your users on the motivation-ability grid, with plot motivation on the vertical axis and ability on the horizontal.Â
Your goal is to identify which behaviors sit above the action line (likely to occur when prompted) and which fall below it (unlikely to happen without intervention).
Each quadrant suggests a different optimization strategy:
- High Motivation / Low Ability: Users want to act but find it too hard. Focus on reducing friction: simplify steps, cut form fields, or provide clear instructions.
- Low Motivation / High Ability: Users could act but don’t feel compelled. Add emotional or social incentives; urgency, exclusivity, or social proof can provide the needed spark.
- Low Motivation / Low Ability: A difficult group to reach. Start with tiny, achievable actions that build momentum and confidence over time.
- High Motivation / High Ability: These users are ready and able. The key is to deliver the right prompt at the right time. Think: timely reminders, nudges, or push notifications that reinforce existing intent.
‍Marketers can use this grid as a diagnostic tool.Â
Whether you’re refining an onboarding flow, crafting a call-to-action, or designing retention triggers, the model helps pinpoint whether the real issue is motivation, ability, or timing.
Use Cases
Consider these three use cases for applying the Fogg Model in marketing and UX:
Mobile App Conversion: Turning Free Users into Paid Subscribers
A user who loves your app (high motivation) but finds the upgrade process confusing (low ability) may stall before converting.Â
Here, a facilitator prompt works best. Simplify the steps (“Try premium free for 7 days, cancel anytime”) and highlight how easy the process is.
Email Marketing: Re-Engagement Campaigns
When users have the ability to return but lack motivation, a spark prompt can reignite interest.Â
Examples include limited-time offers, new feature announcements, or personalized “We miss you” messages that play on curiosity and belonging.
Habit Formation & Retention
To turn one-time users into repeat users, chain smaller prompts that build consistency, such as daily streaks, achievement badges, or contextual reminders (“You’re halfway to your goal!”).Â
Over time, these micro-prompts move users above the action line by steadily increasing both motivation and ability.
Limitations, Critiques, & Considerations
Like any behavioral framework, the Fogg Behavior Model simplifies reality, and that simplicity is both its strength and its weakness.Â
While it’s incredibly useful for understanding immediate, observable actions, it doesn’t capture every nuance of human decision-making.
Here are a few known limitations of the Fogg Model:
Exclusion of Outside Factors
One common critique is that the FBM underplays unconscious and environmental factors. Real-world behavior is shaped not only by motivation, ability, and prompts, but also by habits, mood, social context, and external constraints.Â
‍A user might ignore a perfectly timed notification simply because they’re distracted, tired, or overwhelmed; variables that the model can’t fully account for.
Single-Behavior Focus
Another limitation is that the model assumes a single moment of behavior: the instant when action happens.Â
This makes it less suited to long, complex, or multi-step behaviors, such as adopting a new lifestyle habit or changing an organization’s culture.Â
‍In those cases, the journey involves multiple prompts, varying levels of motivation, and feedback loops that evolve over time.
Action-Orientation
Similarly, the model struggles to capture deeply reflective or identity-based change, the kind that requires introspection or belief shifts rather than quick behavioral nudges.Â
‍Getting someone to click a button is one thing; inspiring them to see themselves differently is another.
Ethical Considerations
Finally, there are important ethical considerations. The same behavioral design principles that make experiences more seamless can also be used to manipulate.Â
Poorly applied, prompts can exploit users’ attention or emotions, leading to compulsive engagement rather than meaningful interaction.Â
‍Marketers using the FBM should therefore aim for transparency, user benefit, and consent, ensuring that their behavior change framework serves the person as much as the product.
Fogg Behavior Model Case Study
Let’s put the model in motion with a simple example: introducing a new feature in a mobile app, like a personal analytics dashboard for tracking user activity.
When the feature launches, the product team notices that adoption is low. Despite strong engagement elsewhere in the app, few users are exploring the new dashboard.Â
‍Using the Fogg Behavior Model, the team breaks down the problem into its three components:
- Motivation: Users might not understand why the feature matters. It’s new, buried in the menu, and doesn’t yet have an emotional hook.
- Ability: The feature requires three steps to access and a short setup process. Manageable, but still enough friction to cause drop-off.
- Prompt: The only cue is a small “New Feature” badge in the navigation bar, which is easy to miss and poorly timed.
In the first iteration of the new feature, users rely on curiosity alone. The small badge appears without explanation, and no context is given for the value of the dashboard. Users with low motivation or limited patience never click through.
‍Applying the Fogg Behavior Model in product design, the team makes three key adjustments:
- Increase Motivation: They add a short message: “See your weekly progress in one glance. Track how far you’ve come!” This appeals to both anticipation (future benefit) and sensation (personal satisfaction).
- Improve Ability: They simplify setup to one click. The dashboard now loads instantly with pre-filled sample data, reducing both time and mental effort.
- Optimize the Prompt: They introduce a spark prompt: a personalized push notification triggered when a user hits a milestone (“You’ve completed 10 sessions. See your progress!”).
‍Within a week of rollout, feature engagement doubles.Â
By aligning their motivation, ability, and prompt model, the team moved the desired behavior, new feature exploration, above the action line.
This hypothetical case study highlights how even subtle design changes, when guided by the Fogg Behavior Model, can turn user inertia into meaningful action.Â
‍Whether launching a new feature, running a re-engagement campaign, or improving checkout flow, the same principles apply: remove friction, activate emotion, and time the prompt just right.
Actionable Steps For Applying the Fogg Model in Marketing and UX
The beauty of the Fogg Behavior Model is that it’s easy to translate into practice.Â
Whether you’re optimizing onboarding, running a campaign, or building new features, the framework gives you a systematic way to uncover why users act, or don’t.Â
‍Here are five straightforward steps to put it in motion:
1. Pick a Key Behavior to Drive
Start with one specific action you want users to take, like upgrading, sharing, completing a setup, or making a repeat purchase.Â
Narrowing the focus makes it easier to diagnose what’s blocking progress.
2. Map Motivation and Ability
Assess where your users fall on the motivation-ability grid.Â
Use data from surveys, interviews, or analytics to understand both their desire (why they would act) and their ease (how simple it feels to act).
3. Identify the Right Lever
Once you know where users sit, decide what needs to shift.
- If motivation is low, strengthen emotional appeal or relevance.
- If ability is low, simplify the task or reduce effort.
- If both are high, focus on timing and delivery of the prompt.
4. Prototype and Test Prompts
Experiment with the three types of prompts (facilitator, spark, and signal) to see which drives the strongest response.Â
Small changes in wording, timing, or placement can dramatically alter outcomes.
5. Monitor and Iterate
Measure engagement and conversion rates after each change. Track where users drop off and refine accordingly. The FBM works best as a continuous feedback loop, not a one-time fix.
‍By cycling through these steps, teams can transform abstract behavioral insights into concrete improvements that boost adoption, retention, and satisfaction, without relying on guesswork.
Bringing Behavior Design to Life
The Fogg Behavior Model (FBM) offers more than just a way to explain user actions. It gives marketers, designers, and product teams a framework to shape them responsibly.Â
‍By balancing motivation, ability, and prompts, you can move users from hesitation to action with clarity and empathy.
At its best, behavior design is about meeting people where they are, understanding what drives them, and making it easier for them to succeed.Â
‍Whether you’re crafting a campaign or optimizing a product flow, Fogg’s simple equation reminds us that meaningful change happens when the right spark meets the right moment.
Lifecycle Marketing 101: Engaging Customers at Every Stage of the Journey
Winning brands don’t just acquire customers, they guide them.Â
From the very first touchpoint to long-term loyalty, the most effective marketers understand that growth isn’t a moment, it’s a journey.Â
Every message, channel, and experience plays a role in shaping that relationship, and how well those moments connect determines whether customers stay engaged or drift away.
This is the essence of lifecycle marketing: a data-informed, stage-based approach to engaging customers from initial awareness all the way to advocacy.Â
Rather than treating marketing as a funnel that ends with conversion, lifecycle marketing views the customer journey as an ongoing cycle that deepens trust, reinforces value, and turns buyers into champions.
Throughout this guide, we’ll explore how to design strategies that meet customers where they are, with the right mix of insight and intent.Â
Two measurement frameworks will serve as our foundation: Multi-Touch Attribution (MTA), which offers granular, real-time clarity into digital performance, and Media Mix Modeling (MMM), which provides the high-level, strategic view needed to plan and optimize for durable growth.
What Is Lifecycle Marketing & Why It Matters
Lifecycle marketing is a holistic, ongoing approach to customer engagement that adapts messaging, offers, and experiences to where each person is in their journey.Â
Rather than treating marketing as a one-time effort to drive acquisition, lifecycle programs nurture relationships over time, from the first touchpoint to the moment a customer becomes a loyal advocate.Â
The goal is simple: increase activation, retention, and advocacy by meeting people with the right message at the right moment.
This approach matters because acquisition alone is rarely sustainable. Studies consistently show that acquiring a new customer is 5-25x more expensive than retaining an existing one, and that even modest improvements in retention can yield exponential gains in profitability.Â
Loyal customers also convert at much higher rates (60-70%) than new prospects (5-20%), spend more over time, and are more likely to recommend your brand to others.Â
In other words, lifecycle marketing doesn’t just keep customers engaged; it compounds value across every interaction.
Measurement Frameworks for Lifecycle Marketing
Measurement frameworks bring this process into focus:
- Multi-Touch Attribution (MTA) reveals which specific touchpoints (ads, emails, content, or campaigns) contribute most along the path to conversion, providing near-real-time clarity at the tactical level.Â
- Media Mix Modeling (MMM), on the other hand, looks at the bigger picture: it quantifies how channels work together across both online and offline environments and shows how changes in budget allocation influence long-term results.Â
Together, MTA and MMM form the analytical backbone of a modern lifecycle strategy, helping teams understand not only what’s working now, but where the next dollar will perform best.
Customer Lifecycle Stages
Every customer journey follows a familiar rhythm: discovery, evaluation, decision, and deepening loyalty.Â
Lifecycle marketing breaks this journey into five key stages, each requiring its own strategies, messages, and success metrics.
Awareness
Awareness is where it all begins: a potential customer realizes a problem or need and starts exploring possible solutions.Â
The goal here is visibility: to appear where prospects are looking and establish credibility before competitors do.
Consideration
Consideration follows once customers begin actively comparing options. They’re weighing features, prices, and proof points.Â
Effective brands provide educational content, case studies, and reassurance that their product is both relevant and reliable.
Conversion (Purchase)
Conversion marks the decision point.Â
This is where trust and friction collide; where a seamless checkout flow, strong social proof, and clear calls to action make the difference between intent and action.
Retention
Retention starts immediately after the first purchase. It’s about value realization and habit formation: ensuring customers see ongoing benefits, stay engaged, and return repeatedly.Â
Thoughtful onboarding, personalized communications, and proactive support are essential at this stage.
Advocacy (Loyalty)
Advocacy represents the highest form of customer engagement, when people not only stay but share.Â
Referrals, reviews, and community participation amplify the impact of every satisfied customer, turning individual experiences into network effects.
Of course, the customer journey isn’t linear. People loop back to earlier customer lifecycle stages, skip steps entirely, or pause midstream.Â
Effective, data-driven lifecycle marketing strategies anticipate that fluidity, adapting outreach and measurement accordingly.
This is where data clarity matters most:
- Multi-Touch Attribution (MTA) reveals which early interactions drive awareness and consideration, and which combinations of touchpoints tend to precede conversion.Â
- Media Mix Modeling (MMM) complements that view by showing how long-term investments in retention and advocacy influence overall revenue performance.Â
- Together, they ensure every stage contributes to sustainable, compounding growth.
Strategies to Engage at Each Stage
Each phase of the customer lifecycle requires a distinct approach. The tactics below outline how to engage customers effectively at every stage and how to measure success using Multi-Touch Attribution (MTA) and Media Mix Modeling (MMM).
Awareness
Goal: Build visibility and credibility as prospects identify their problem or need.
Tactics:
- Publish thought-leadership content and SEO-optimized articles.
- Leverage social media and PR for category awareness.
- Offer light-touch lead magnets such as quizzes, resource guides, or newsletters.
Measurement:
- Optimize the customer journey with multi-touch attribution to compare which channels and creatives generate the highest-quality first touches.
- Feed performance insights back into content and media planning cycles.
Consideration
Goal: Provide proof, reassurance, and clarity as prospects compare solutions.
Tactics:
- Share case studies, testimonials, and comparison guides.
- Host webinars or interactive demos.
- Use retargeting ads or nurture emails to stay top of mind.
Measurement:
- Apply MTA to understand how different combinations of touchpoints (e.g., content -> email -> retargeting) move prospects closer to conversion.
Conversion (Purchase)
Goal: Remove friction and reinforce confidence at the moment of decision.
Tactics:
- Simplify UX and checkout flows.
- Highlight trust signals (reviews, guarantees, secure payment icons).
- Deliver timely nudges like cart reminders or limited-time offers.
Measurement:
- Use MTA to pinpoint where users drop off and which final interactions drive conversions.
- Track assisted conversions, not just last-click results, to capture hidden influence.
Retention
Goal: Strengthen loyalty through ongoing value and engagement.
Tactics:
- Build onboarding sequences that accelerate time-to-value.
- Trigger lifecycle emails around product usage or milestone events.
- Offer loyalty programs, personalized perks, and proactive support.
Measurement:
- Use MMM to estimate the incremental lift of retention programs.
- Calibrate spend by cohort or segment to optimize ROI.
Advocacy (Loyalty)
Goal: Turn satisfied customers into brand champions.
Tactics:
- Launch referral programs and incentives.
- Spotlight user-generated content (UGC) or customer success stories.
- Encourage reviews and community participation.
Measurement:
- Apply MMM to model long-term revenue effects of advocacy.
- Compare marginal loyalty investment vs. incremental acquisition spend to find balance.
Tools & Channels for Lifecycle Marketing
Behind every effective lifecycle marketing strategy is a strong operational backbone: the systems, data, and tools that make personalized engagement possible.Â
These components work together to deliver the right message to the right customer, at the right time, across every stage of the journey.
Data Foundation
Purpose: Build a single, accurate view of the customer to enable precise targeting and measurement.
Key Elements:
- Event tracking: Capture key behaviors such as sign-ups, purchases, and feature usage.
- Identity resolution: Connect anonymous and known user data across devices and sessions.
- Unified profiles: Merge behavioral, transactional, and demographic data to identify lifecycle stage and engagement patterns.
Automation
Purpose: Deliver timely, personalized experiences at scale.
Key Capabilities:
- Journey builders: Create dynamic workflows that adapt to user behavior or stage transitions.
- Behavioral triggers: Automate responses based on recency, frequency, or inaction.
- Segmentation rules: Update audiences automatically as customers progress through the lifecycle.
Channels
Purpose: Communicate consistently across touchpoints while honoring user preferences.
Primary Channels:
- Email: Still the most reliable owned channel for retention and loyalty.
- In-app & push/SMS: Ideal for real-time engagement and usage reminders.
- Paid & retargeting: Re-engage or re-activate customers across platforms.
- Website personalization: Adapt content dynamically to match user behavior or intent.
- Community & social spaces: Encourage advocacy and deepen connection beyond transactions.
Measurement Frameworks
Purpose: Evaluate performance across both granular and strategic horizons.
Multi-Touch Attribution (MTA):
- Tracks user-level interactions across digital touchpoints.
- Enables rapid optimization, creative testing, and budget rebalancing within channels.
Media Mix Modeling (MMM):
- Analyzes aggregate performance across online and offline media.
- Accounts for seasonality, saturation, and external factors.
- Guides medium- and long-term budget planning and scenario testing.
Together, these tools and frameworks create a connected ecosystem that captures, automates, and measures every customer interaction throughout the lifecycle.
Implementation Considerations
Even the best lifecycle strategy can fall apart without strong operational discipline.Â
Successful programs depend on shared definitions, consistent rhythms, and a clear feedback loop between marketing, product, and customer success teams.
Shared Definitions
Clarity starts with language. Every team should agree on what qualifies as a new user, an active user, or a churned user, as well as when customers enter and exit each lifecycle stage.Â
Standardizing attribution windows and engagement thresholds ensures that everyone is evaluating performance from the same baseline. Without this alignment, teams risk drawing conflicting conclusions from the same data.
Cadence
Set a sustainable rhythm for measurement and decision-making.Â
Multi-Touch Attribution (MTA) insights work best on a weekly cycle, supporting fast iteration on creative, targeting, and friction fixes.Â
Media Mix Modeling (MMM) operates at a monthly or quarterly cadence, guiding high-level decisions on budget distribution, channel mix, and seasonal optimization.Â
This dual timing keeps teams responsive in the short term while steering long-term efficiency.
Product
RESOURCES
Support
Legal
Follow us
.svg)
