How to Improve Client Engagement in Your Digital Product

To improve client engagement, find the exact moments where people stop getting value from your product, fix those moments first, and measure whether behavior changes. Messaging campaigns, loyalty perks and chatbots can help, but in a digital product most engagement is won or lost inside the product itself: in onboarding, in feature discovery and in the small frustrations that never reach your support inbox.

This guide is written for product managers, designers, developers, UX researchers and marketers. It covers what engagement means, how to locate friction, which tactics work in onboarding and everyday use, how to collect feedback, which metrics to watch and how to run all of it without crossing privacy lines.

What client engagement means in a digital product

The term is used loosely, and that is a real problem. A 2025 CHI systematic review of 241 papers found significant definitional inconsistencies and recommends treating user engagement as a category label rather than one unified construct. In practice that means you should decide what engagement means for your product before you try to raise it.

Academic work gives a useful starting point. A 2025 systematic literature review describes digital customer engagement as the online behaviors customers show toward a brand beyond the purchase itself: sharing, recommending, reviewing, posting. It treats loyalty as an outcome of that engagement, not a substitute for it. Pansari and Kumar’s 2016 framework ties engagement to satisfaction and emotional connection, and separates direct contributions (purchases) from indirect ones (referrals, feedback).

For a SaaS or app team, a working definition might be: the share of your clients who repeatedly reach the outcome they signed up for, and who tell you or others about it. That definition points at behavior you can observe, which is what you will improve.

Why it pays

The commercial case is well supported. A meta-analysis of 184 publications, covering 146,380 observations, found links between attitudinal engagement and loyalty, and between behavioral engagement and firm performance. IBM notes that engaged customers are less likely to churn and that acquiring a new customer costs four to five times more than keeping an existing one. If you want to see how that plays out for subscriptions, our guide to reducing churn step by step picks up from here.

Experience feeds engagement, too. A 2022 study of 189 online shoppers published in Frontiers in Psychology found that online customer experience strongly influenced engagement, which in turn improved loyalty. It is a small sample from one country, so treat it as direction rather than a benchmark, but it matches what product teams see daily: a smoother experience, more engaged clients.

Step 1: Find out what clients need and where they get stuck

You cannot improve engagement in general. You improve it at specific points. The first job is to locate them, and the most reliable method combines two kinds of evidence. Atlassian’s guidance for product teams describes direct feedback such as surveys and interviews, plus indirect behavioral data like usage patterns, churn indicators and adoption trends.

Ask about the present, not the future

Problem discovery interviews work best when they explore how a person handles an obstacle today, rather than testing whether they like your idea. Scrum Manager’s discovery guide frames it exactly that way. Open prompts such as “Can you walk me through your process?” and follow-up questions, as Product School recommends, tend to surface real pain points that a yes/no survey hides.

Watch what they actually do

Interviews tell you what people remember. Behavior tells you what happened. Friction is often invisible in aggregate numbers: a funnel shows that 40% of people drop at step three, but not whether they were confused, hit an error or got distracted.

Checkout is the classic example. Baymard Institute’s research on US shoppers found that 48% had abandoned an order because of high extra costs and 22% because of slow delivery, and that half of sites leave fulfillment options out of the selection interface. Those are friction points a team only fixes once it sees them.

Session replay is built for this gap. Watching a handful of sessions from users who abandoned a flow shows rage clicks, dead ends, repeated back-and-forth and form errors. Heatmaps then show whether the pattern holds across everyone. Our heatmap and click map tools are designed for that second check, and our piece on behavioral product analytics metrics explains which signals to look at first.

A practical routine:

1. Pick one funnel step with a notable drop-off.

2. Watch 10 to 20 replays of users who dropped there.

3. Write down what each person tried to do, not what you think they should have done.

4. Group the notes into three or four causes and rank them by how many clients each affects.

5. Fix the top cause, then compare the drop-off before and after.

Step 2: Make onboarding deliver value fast

Onboarding is where engagement habits start, and it is the cheapest place to intervene. Reforge’s guidance is to connect new users to the core value proposition, ask only for the information needed to experience it, and define activation around the moment users first see that value, the “Aha Moment.”

What that looks like in practice:

• One task at a time. Nielsen Norman Group recommends presenting a single task per step, showing progress and offering contextual help throughout.

• Chunk complex tools. For complicated products, NN/g advises breaking onboarding into manageable portions and offering help on request rather than sending people off to search elsewhere.

• Cut every field you do not need yet. Each extra question is a reason to leave. Collect the rest after the first success.

• Define activation in behavior. “Created first report” or “invited a teammate” is measurable. “Understands the product” is not.

When you redesign a flow, watch real sessions before and after. Our article on improving onboarding with session replays walks through how teams spot the exact screen where new users stall. And once people are activated, product adoption strategies help you move them from one feature to the several that make a product sticky.

Step 3: Personalize and communicate without being intrusive

Personalization raises engagement only when it feels helpful. The risk is interruption. NN/g notes that tutorials can interrupt users, and that Clippy failed because it was intrusive and often guessed users’ goals wrongly.

Their alternative is contextual help built on progressive disclosure: visible without overwhelming, easy to dismiss and easy to find again later. A few rules follow:

• Trigger help from what a person has actually done, not from assumptions about their role.

• Always provide a dismiss control, and remember the choice.

• Keep a persistent help entry point so nobody has to rely on a message they closed.

• Send fewer, more specific emails and in-app messages, each tied to a behavior such as an unfinished setup step.

If you overlay chat or support tools on your product, check replays to see whether prompts cover buttons or pull people away from the task they came to complete.

Step 4: Collect feedback and close the loop

Yale’s usability team lists a wide set of feedback channels: interviews, user testing, support requests, focus groups, analytics and surveys. They argue that direct feedback supplies the reasons, confusion and unmet needs behind observed clicks, so it belongs next to analytics rather than replacing it.

For ongoing programs, Aha’s guidance on voice of the customer recommends continuous listening across surveys, interviews, tickets, sales conversations, reviews and usage data, followed by structured synthesis, a clear link to decisions and closed-loop communication.

The last part is the one teams skip. When a client reports a problem and you fix it, tell them. It proves that feedback has an effect, and that makes people more willing to give it again.

A simple loop:

1. Tag every piece of feedback with the product area and the client segment.

2. Review tags monthly and compare against behavioral data. Do complaints match where people drop?

3. Pick the two or three themes tied to real behavior.

4. Ship, then message the people who raised them.

5. Check the same metric after release.

Step 5: Measure engagement with a scorecard

Pick a small set of metrics across three layers. ThoughtSpot’s guidance suggests a scorecard with behavioral signals such as DAU, WAU, MAU and feature exploration, friction indicators such as support tickets and abandonment points, and business outcomes such as renewals and expansion revenue, watched regularly while you test changes like new onboarding sequences.

The ratio of daily to monthly actives is a quick stickiness read, and our guide to calculating DAU, MAU and WAU explains how to compute and interpret it. For a broader view of how teams read usage data, see product usage analytics in SaaS. Early warning signs that engagement is slipping are covered in key customer churn indicators, and the money side in revenue analytics for SaaS.

Two cautions. First, no number here is a universal benchmark: healthy engagement depends on whether your product is used daily or quarterly. Compare yourself with your own past, by cohort. Second, a metric that rises is not proof of improvement. A new notification can lift daily actives while lowering satisfaction. Pair every metric with a replay review or a short survey.

If you want a technology-focused view of how teams track engagement across the customer journey, this overview of improving user engagement is a good companion to the scorecard above.

Our perspective: engagement is a debugging problem

We build analytics for product teams, so we watch a lot of teams try to raise engagement. The pattern that works is rarely a campaign. It is a habit of looking closely at one broken moment, fixing it and checking the result.

We believe numbers and observation need each other. Quantitative data tells you where to look: which step, which segment, which release. Qualitative data, such as a replay of a person fighting a form, tells you why. Teams that rely only on dashboards debate causes. Teams that rely only on anecdotes fix whatever the loudest client mentioned. Together they let a product manager, a designer and a developer look at the same evidence and agree on what to do next.

We also think privacy is part of the craft, not a tax on it. Clients who trust that you handle their data carefully engage more openly, and a tool that masks sensitive fields by default makes it easier to say yes to behavioral research inside your company.

Step 6: Test changes and respect privacy

Every tactic above involves watching behavior, so privacy has to be designed in. The UK Information Commissioner’s Office advises mapping personal-information needs at kick-off and considering data protection throughout research, design, development, launch and post-launch, including when you test work in progress. It also stresses obtaining valid, clear consent during design. That is UK guidance, so check the rules that apply in each market you serve, such as GDPR in the EU and CCPA in California.

Consent interfaces are easy to misread. In an ICO study of consent-or-pay choices, 18% of UK internet users wrongly believed no data would be collected when they chose the consent option. Write consent copy in plain words and test that people understand it.

Practical habits for engagement research:

• Mask or exclude fields that hold passwords, payment details and other sensitive input.

• Collect only the behavior you will act on.

• Limit who can watch recordings and how long they are kept.

• Run changes as controlled tests, such as a new onboarding sequence for half of new sign-ups, so you know the change caused the result.

• Involve legal or your data protection officer before launching new tracking, especially for audiences in several jurisdictions.

How LiveSession helps

LiveSession combines session replay, heatmaps, conversion funnels, error tracking and event-based analytics in one place, so you can move from a drop-off in a funnel to the sessions behind it without switching tools. It integrates with tools such as Intercom, Zendesk, Shopify and Segment, and it is built with GDPR and CCPA compliance in mind.

Plans on our pricing page start with a Free plan at $0 per year, followed by Basic at $54 per year and Pro at $83 per year. Enterprise pricing is not published. To see what a drop-off analysis looks like, explore the product analytics dashboard, or read how to improve your product engagement score with session replay.

FAQ

What is a client engagement strategy?

It is a plan for how you help clients reach value, keep returning and give you feedback. It includes defining engagement for your product, finding friction, improving onboarding and communication, and measuring results. The best strategies rest on observed behavior, not assumptions.

How do you drive positive client engagement?

Start where clients struggle. Cut onboarding to the steps that lead to the first win, use contextual help instead of interruptions, and close the loop on feedback. Then check your scorecard to confirm behavior changed.

Which metrics show whether engagement is improving?

Watch behavior (DAU, WAU, MAU, feature usage), friction (abandonment points, support tickets) and outcomes (renewals, expansion revenue). Compare against your own history by cohort rather than against generic benchmarks.

How is increasing consumer engagement different from client engagement?

The principles are the same: reduce friction, deliver value early, communicate with relevance. Consumer products tend to involve more users, shorter journeys and more reliance on aggregate behavioral data. B2B clients often need account-level views and more direct conversations.

Can I analyze engagement without breaking privacy rules?

Yes, if you plan for it. Map the personal data you need, collect consent clearly, mask sensitive inputs and restrict access to recordings. Confirm local requirements with your legal team.

Sources

• What is User Engagement? A Systematic Review of 241 Papers (CHI 2025)

• Digital customer engagement: A systematic literature review

• Customer engagement: the construct, antecedents, and consequences

• A meta-analysis of customer engagement behaviour

• What is customer engagement? | IBM

• Online Customer Experience Leads to Loyalty via Customer Engagement

• Customer Feedback: A Guide for Product Teams

• Product discovery (Scrum Manager)

• Customer Discovery: How Product Teams Lead the Charge

• Include All Order-Fulfillment Options in the Selection Interface (Baymard Institute)

• Optimize new user onboarding (Reforge)

• Onboarding and Connecting Smart Devices: 5 Guidelines (NN/g)

• New Users Need Support with Generative-AI Tools (NN/g)

• Onboarding Tutorials vs. Contextual Help (NN/g)

• Collect Feedback (Yale Usability & Digital Accessibility)

• Voice of the Customer Programs (Aha!)

• How to Build a User Engagement Strategy (ThoughtSpot)

• Privacy in the product design lifecycle (ICO)

• Exploring people’s understanding of and attitudes towards consent-or-pay (ICO)