It doesn’t take long on your smartphone before something starts to annoy you. Product tours that interrupt workflow. Tooltips that appear at precisely the wrong moment. Survey requests that popup just as users are trying to complete crucial tasks. We’ve all experienced the frustration of being bombarded with messages intended to help but instead become obstacles.
The problem isn’t the concept of in-product guidance itself, it’s the execution.
Most app developers deploy these tools based on assumptions rather than evidence, creating experiences that feel random, untimely, and irrelevant to users.
Popups have a bad reputation for being annoying, intrusive, and irrelevant, and consumers close them as quickly as possible. The sentiment reflects a wider industry challenge, how do we guide users without constantly annoying them?
The annoyance economy
Every digital interaction carries an invisible cost — the cognitive load it places on users.
When guides, tooltips, and surveys appear without consideration for context, timing, or relevance,
they rapidly deplete this limited resource.
According to Forrester’s 2024 US Customer Experience Index, customer experience quality has declined for the third consecutive year, reaching an all-time low.
The decline is significant, as research indicates that devoted customers are willing to pay 50% to 200% more to stay with a brand. Negative interactions do more than annoy users — they gradually erode user confidence and brand loyalty.
How AI changes the game
Delivering timely guidance used to be nearly impossible. Humans simply cannot predict the perfect moment for every user across countless scenarios. But this is where artificial intelligence is changing the equation to address customer frustration.
By leveraging behavioural data, companies can implement ‘annoyance monitoring’ — systems that track user reactions to guidance and optimise timing, frequency, and content accordingly. These systems analyse patterns of engagement, abandonment, and user sentiment to determine when guidance is helpful versus when it’s disruptive. It’s the difference between hurling the same letter at every one of your customers, versus tailoring what you say based on how they reacted to your last message.
Setting new rules for better engagement
To create effective in-product guidance, companies must move beyond arbitrary triggers and focus on relevance, personalisation, and measurable impact.
Guidance should be triggered by user behaviour rather than set timelines, ensuring that prompts appear only when they are genuinely helpful. Tailoring experiences to different user segments is also crucial. First time users need onboarding, while experienced users may benefit more from advanced feature tips or workflow optimisations.
Measuring success requires looking beyond surface-level engagement metrics. Click-through rates or tooltip views mean little if they don’t contribute to user satisfaction. Instead, companies should track outcomes. For example, whether guidance helps users complete key tasks or make additional purchases.
Additionally, information should be introduced progressively, revealing itself as users demonstrate readiness. This prevents cognitive overload while keeping support accessible at the right moments.
Companies adopting this approach are already seeing significant improvements. McKinsey research indicates that retailers implementing personalisation see revenue increases of 10% to 30%, highlighting the direct impact of tailored user experiences on business growth. By respecting user context and needs, businesses can drive engagement without frustrating their customers.
The human touch
Despite AI’s ability to optimise timing and relevance, the most effective guidance strategies still rely on human empathy. Data-driven insights determine the right moment to engage, but only a human perspective ensures the tone, and approach feels genuinely helpful rather than robotic.
Users don’t just want efficiency, they want experiences that feel personal and yet still considerate of their needs. Thoughtful design choices, like offering users control over how and when they receive guidance, help make interactions feel more like assistance than directives.
Transparency also plays a key role. Users should always understand why they are receiving guidance and how it benefits them.
The future of in-product guidance isn’t eliminating interruptions, it’s ensuring each one delivers real value. Companies that master this balance will stand out not just for their efficiency but for fostering deeper user trust.