This is a 5-part series
Click below to navigate to the next chapter.
In the previous chapter we discussed some of the challenges around understanding user behaviour on mobile. These span from challenges around reliable user identification, attributing in-app user activity to marketing touch points and the wider customer journey as well as the dependency on developers to instrument tracking and the often web-centric approach to analytics of many packaged analytics tools. Given these challenges, approaching mobile analytics requires an investment both from a resources and time perspective. In this chapter, we will dive deeper into the opportunity we see for businesses when they make this investment, and why we believe deeply understanding user behaviour on mobile should be a priority for businesses in 2021.
Users expect mobile-first experiences
In the first chapter of this series, we highlighted that in 2016, internet usage on mobile devices overtook desktop in mature markets such as the UK. Data suggests that in emerging markets, mobile internet usage is even more prevalent, and accounts for more than 75% of total usage. But what does this mean for businesses?
We have reached the stage where optimizing the digital presence for mobile is no longer optional. In their 2020 report titled ‘Milliseconds Make Millions’, Deloitte show that even small changes towards improving a brand’s mobile experience (including site speed) can have a significant impact on a company’s bottom line. Surveying a sample of retail, travel, luxury and lead generation brands across Europe and the US, they found conversions increased by 8-10% due to such improvements.
Let’s look at a few examples from their report. By prefetching assets and search results based on user flows through their site, Ebay improved loading times and streamlined their user experience. They observed a 0.5% increase in add-to-cart count for just a 0.1 second improvement in load time. Pharmaceutical giant Pfizer completely rebuilt their site infrastructure to allow them to develop dedicated mobile experiences, reducing bounce rates by 20%. Risa Wexler, Head of Pfizer’s Media Lab, said “It’s critical to build for each platform so you’re providing the experience people expect, regardless of the platform on which they seek your information”. These examples highlight how tailoring experiences to mobile devices can have significant business impact. But in order to optimize experiences in this way, companies need to develop a deep understanding of how their users interact with their digital platforms.
Mobile analytics is no longer a nice to have
It is essential for businesses to have robust analytics in place to help them understand how users interact with their digital products. It enables them to deliver rich, relevant experiences, and that is key to success in today’s competitive world. Google goes as far as to say “Brands are no longer competing with the best experience in their category, they are competing with the best digital experience a consumer has ever had.”
Specifically, getting a better understanding of how users interact with mobile applications allows companies to understand who is interested in their products, content or services, and why. In turn, this enables them to target the right users on the right platforms, and then serve them highly relevant and compelling marketing, increasing the ROI on marketing activities.
It also allows companies to understand exactly how users are engaging with their products, i.e. what functionality they enjoy most and where they encounter friction. These insights can be used to craft rich and valuable experiences that increase user engagement, therefore supporting retention and decreasing churn. And it’s not a one-off process. Observing user behaviour as well as app performance enables continuous improvement of the user’s in-app experience.
Key use cases
In their 2016 report on ‘Competing in a data-driven world’, McKinsey estimates that real-time optimisation and radical personalization are the two most valuable data use cases for companies to tackle. Both involve developing a deep understanding of user behavior, and using that understanding to alter user experiences dynamically. However, that understanding can power a plethora of use cases across the business. Most analytics use cases on mobile can broadly be narrowed down to three: marketing analytics, product analytics and performance analytics.
Marketing analytics primarily focuses on understanding the effectiveness of various marketing channels and efforts in driving user acquisition and conversion. In order to evaluate the ROI on their marketing spend, companies typically measure the cost per install (CPI) and customer lifetime value (CLV), i.e. the value a customer will bring over time. Being able to identify the channels that perform best, as well as the users that will be most valuable long term, enables companies to use their marketing budgets more effectively to drive user acquisition. In short, robust marketing analytics on mobile can be the difference between wasting substantial budget versus driving sustainable growth.
Product analytics enables companies to understand how users engage with their mobile applications. While businesses often start by measuring simple metrics such as daily active users over time, more granular data on in-app behaviour allows companies to identify what functionality or customer journeys drive conversions and retention. For example, this data can be used to determine what content or functionality should sit behind a paywall, what products a user is recommended or what discounts they are offered. Optimizing the mobile experience accordingly, companies can increase customer lifetime value and reduce churn.
As user attention span shortens, companies need to ensure their mobile experience is fast, reliable and seamless. To deliver such experiences, they need to closely monitor app performance, including load times, errors and crashes. Furthermore, capturing this data alongside broader user behavioural data enables companies to identify what impact performance issues have on user engagement and thus KPIs such as conversions or retention.
Across these different use cases, developing a deep understanding of user behaviour on mobile can be the difference between a company that can outgrow their competitors and one that struggles to keep pace with the needs of their users. Thus, companies need to develop a robust strategy for mobile analytics, and invest in the right people, tools and processes to ensure their mobile experiences hold up to the competition. In the next chapter, we will outline the Snowplow approach to mobile analytics, and how you can use the Snowplow technology to reliably capture and identify user behaviour across your entire customer journey, including in your mobile applications.