Marta Sulkiewicz on Data-Driven Digital Strategy at Similarweb

1. What role does real-time data play in optimizing digital marketing performance across web and mobile?

Many businesses rely on first-party data, typically available in real time or with minimal delay, in order to optimize their performance]. However, businesses don’t operate in isolation—you need market context, competitor insights, and consumer behavior trends to understand why your metrics are shifting and how to respond. This is where market intelligence comes in.

Traditionally, this data was siloed, delayed, and lacked actionability. Now, real-time insights enable brands to react instantly to shifting demand and competitor moves. For example, during the 2024 U.S. elections, Similarweb observed a surge in crypto-related searches, followed by increased downloads and engagement in crypto trading apps like Robinhood. The app even rebranded itself in the App Store to "Now with Election Market" on November 3rd—an agile response to market needs. That’s one reason Robinhood was able to outperform competitors on important measures of engagement such as daily stickiness (the ratio of daily to monthly usage) and sessions per user.

2. How does unifying web and app analytics help businesses create a more comprehensive digital strategy?

Consumers interact with brands across multiple touchpoints - web, mobile apps, and offline channels. A customer might see an ad on TV, search for the brand on Google or ChatGPT, download the app from the store, and then make a purchase. For example, email marketing may drive users to a website, where a promo code encourages app activation. And of course these days we are observing referrals from AI-driven platforms like ChatGPT influence user journeys as well.

Without a holistic view, businesses miss critical insights and unique opportunities to acquire customers and generate revenue. It can be easy to misinterpret market trends or business performance – for example, a decline in website traffic might not indicate a market downturn but rather a shift toward mobile app adoption. Similarly, tracking loyalty program sign-ups in an app alongside segment-level website traffic provides a fuller picture of customer behavior. Understanding both web and app data is key to an effective digital strategy.

3. What challenges do companies face when integrating cross-platform data insights, and how does your solution address them?

The biggest challenge to integrating cross platform insights is data normalization - ensuring fair comparisons between web and app metrics. Web visits and app sessions aren’t identical, as app sessions often reflect deeper engagement. To bridge this gap, we provide frameworks and dashboards that align engaged web visits with app interactions, making cross-platform analysis more accurate and actionable.

4. How does AI improve the accuracy of app performance benchmarking and competitive analysis?

AI is a game-changer in market intelligence. By processing petabytes of data, Similarweb enhances estimation models for competitor benchmarking, delivering more precise insights than ever before. We leverage AI to analyze and categorize customer reviews, automatically clustering feedback into key themes providing a fast and detailed understanding of user sentiment. We’re also continuously integrating AI-powered insights to accelerate decision-making and improve competitive intelligence products, working on AI agents right now, so stay tuned!

5. What key KPIs should brands track to optimize mobile and web experiences?

The right KPIs depend on your business goals. If you’re looking to increase engagement, consider focusing on metrics like daily stickiness (daily active users comapred with monthly active users for apps, and the ratio of daily visitors to monthly visitors for the web), time spent per user, exclusive and returning visitors on website, app ratings, sentiment trends, and retention on apps. For customer acquisition efficiency, we would consider a different set of KPIs such as  paid traffic versus bounce rate on web, and store downloads versus 30-day retention for apps.

When integrating market intelligence with your first-party data, it's important to put absolute numbers into context. Calculate your share within the market and compare it to competitor averages. It’s also valuable to analyze the performance of top players in your category. By aligning KPIs with your business objectives, you can build a more effective optimization strategy. Enriching your data with full market context not only shows how you're performing - it also helps explain why it’s happening and what actions you can take.

6. How can businesses use predictive analytics to anticipate trends in user engagement and behavior?

Similarweb provides daily behavioral insights and can even get down to the hourly level for keyword trends data. On the other hand, historical trends have great predictive value—seasonal patterns, advertising spend from market leaders, consumer demand shifts, and broader economic sentiment, all of which contribute to better forecasting. By layering these insights, businesses can anticipate trends and proactively adjust their strategies.