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Asia Pacific’s insatiable appetite for innovation and convenience is fueling the growth of digital economies throughout the region. In fact, IDC predicts that by 2026, 40% of total revenue for the top 2,000 Asia-based organizations will be generated by digital products, services, and experiences. With digital products here to stay and the economic outlook uncertain, businesses are under pressure to innovate within tight budget constraints.
Thankfully, for many businesses operating in this digital age, there’s one thing they can control in order to attract and retain customers – their digital product. Whether you’re Grab, Shopee, or DBS, your app is an integral part of your customer’s experience and relationship with your brand. This means that in order to keep users happy and coming back, businesses must constantly refine their digital product experience.
To do this, businesses need to know where and when to make the right bets on their product. And while that may sound like a daunting and nebulous task, the starting point is actually much more accessible than you might think: data.
Sitting on a data goldmine
For the longest time, businesses have been lectured on the importance of data collection – and the experts who preached this mantra weren’t wrong. Fast forward to today, and many businesses find themselves sitting on a mountain of product and customer data that now holds the key to delivering amazing digital experiences.
But it’s not enough to just accumulate an abundance of data. Now, businesses must start drilling into that mountain to surface actionable insights that will propel growth. What is the data telling them about what customers want, what their pain points are, and what companies must do to not just meet but exceed customer expectations?
Only by uncovering clear and timely insights about how customers interact with their apps can businesses modify and optimize their digital products accurately to meet the needs of their users. With time, continued analysis, and constant optimization, businesses will find that their digital products consistently hit the mark with each new tweak, slowly becoming an indispensable part of their customers’ lives.
Measuring what matters most
The sheer wealth of data available these days can be intimidating for businesses looking to make sense of it all. This is especially tricky when it comes to reconciling how data relates to the bottom line. For decades, businesses have been relying on surface-level metrics like page clicks and views to measure success. The problem is these metrics don’t tell the whole story and could only provide superficial – and often unactionable – insights. In other words, businesses know the “what”, but never the “why”.
Now, businesses can use data to bring them much closer to the driving force behind their success: customer satisfaction.
In practical terms, this means rethinking their growth strategy to tie closely to what their product data is telling them about customer behavior. They’ll need to stop relying on vanity metrics and start tracking insights like where and when customers are successfully converting, what actions in the product ultimately lead to a sale, or what your best customers have in common. To pull this off, businesses must integrate their product data with analytics, so that tracking progress is as easy as clicking a button.
Take Jumbo Interactive, the Australian lottery company, as an example. In the past, Jumbo’s marketing team would cast a wide net, frequently blasting their customers with emails. And while some of these customers would end up buying more, conversion rates remained low. They wanted to take a personalized approach to boost conversions and secure more sales, but they didn’t know how to get there.
In comes the power of data. Jumbo Interactive started digging deeper into their product data to uncover granular details about their customers’ interaction with their platform. This allowed them to segment customers into different cohorts, and then use AI to provide personalized recommendations. For example, the data showed that suggesting the Play page to charity lottery ticket buyers often led to purchase delay, as this group would often spend a lot of time on the Play pages, looking at the homes and vehicles being raffled – instead of buying tickets.
So, Jumbo Interactive’s team rolled out an email campaign that directed charity lottery ticket buyers to the online shopping cart instead. They would then retarget those who had indeed bought a ticket with AI-generated follow-up recommendations and push notifications. With this new approach, the team found that the email had a 20% improvement over control, and the app push had a 32% improvement over control. Within just two months of Jumbo offering AI-driven recommendations, they experienced a 158 percent lift in conversions on one checkout page. This has the potential to translate to an extra $500,000 in new revenue opportunities year over year.
Equipping everyone with the power of data
Once businesses have decided which elements of their product data to prioritize and track, the next step is ensuring that everyone within the business can easily translate that data into actionable insights.
When digitalization was in its infancy, data collection was typically driven by a single team of analysts, tasked with extracting, manipulating, and then presenting dense data into easy-to-understand reports. As digital transformation started to pick up speed across industries, this model proved difficult to scale.
Now, businesses must make sure the right data is easily accessible to everyone. But just as not all data is created equal, not everyone will have the same level of data literacy. This is where self-service data analytics capabilities can bridge that gap.
Product and growth teams cannot rely solely on data teams. With self-service tools, anyone – regardless of their aptitude or familiarity with data – can build an easy-to-use dashboard for themselves and access insights in a few minutes. Such tools are especially useful when companies are trying to do more with less. When different teams across the entire business have a one-glance view of how customers use the product and its features, they can quickly pivot and tweak their strategies according to what the data is telling them.
Once you have everyone speaking the same language about your data, you can make data-driven decisions faster. This empowers teams to identify and fix customer problems faster, react swiftly to customer requests, and test the impact of new product features in a scalable manner.
Turning gold into growth
Great products are built with great data. But this can only happen if companies are prioritizing the right data, and if everyone across the organization – from product, to marketing, to sales – can make sense of it. We’ve moved beyond data collection and now, more than ever, it’s crucial that companies use all tools at their disposal to not just survive but thrive. This includes digging deep into product data, and consistently delivering quality experiences that outshine the competition.
By harnessing the power of data to constantly improve your product, and then letting your product speak for itself, businesses can drive product-led business growth that is sustainable even amid economic uncertainty.
Mark Velthuis, the vice president of APJ at Amplitude, wrote this article.
The views and opinions expressed in this article are those of the author and do not necessarily reflect those of CDOTrends. Image credit: iStockphoto/Nordroden
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