Strategy & Organisation
How data is transforming the e-commerce industry
As e-commerce has dominated the market throughout the last year, digital retailers have become overwhelmed with data. Across all industries, around 88% of products added to online baskets around the world do not convert to purchase. Closer to home, Brits abandon online baskets worth almost £30 a month, resulting in more than £18 billion of lost sales each year. Despite this, 270 million online card transactions worth £22 billion were made in the year up to December 2020, an 8% increase on the year previous. Without even considering individual brands’ websites, app and customer insights, this data presents huge challenges and opportunities for digital sellers.
In the new digital reality, consumers’ expectations are high and attention spans are low, putting pressure on brands to engage and secure sales at rapid speed. At the same time, tried and tested methods (like social media marketing and retargeting) are becoming more expensive and less effective. As a result, it’s increasingly difficult to attract, convert and retain customers. But a data-driven e-commerce strategy could be the solution. McKinsey reports that data-driven organisations are 23 times more likely to acquire customers, 6 times as likely to retain them and 19 times as likely to be profitable.
Online retailers have an abundance of data at their disposal from a multitude of sources, yet very few of them are leveraging it in the best ways. We’ve outlined how data is transforming the e-commerce industry and how businesses can create opportunities from their insights to gain competitive advantage.
Leading the pack
While data-driven strategy has become more of a buzzword in recent years, the e-commerce giants are understood to have been extracting and applying data to inform their approach for some time. As early as 2013, 35% of Amazon sales were generated by data-driven insights, so there’s certainly some catching up to do.
Enterprise retailers like Amazon have the benefit of huge financial resources that enable them to hire the best data talent and adopt the most innovative technologies at rapid speed, a privilege that the majority of e-commerce brands don’t have. And although we can admit that Amazon is in a league of its own, brands can certainly take inspiration to find actionable insights within their data. As the old adage goes: if you can’t beat them, join them.
Benefits on offer
There are many reasons why 60% of e-commerce merchants told Forrester they’re stepping up their digital operations investment. Effectively analysing data and actioning insights offers a raft of benefits to help e-commerce brands improve performance and cut through the noise in the market:
- Precision – A data-focused strategy eliminates guesswork, allowing businesses to make informed decisions based on facts rather than instinct or opinion; driving sales by leveraging past trends to make future predictions.
- Agility – With a strong data framework in place, companies are in a better position to adopt a test and learn approach as well as react quickly to real-time market and customer trends.
- Cost efficiency – A data-driven strategy provides businesses with crucial insights that maximise sales and minimise spend; from what products are performing well to the optimum channels to push them to customers.
- First mover advantage – Despite a strong belief that data will be the cornerstone of operations in the very near future, the majority of brands are yet to embark on their data journey. Those that have, or do very soon, are in a position to gain first-mover advantage
Creating new possibilities
E-commerce data pools are vast. They consist of customer behaviour, stock levels, product insights and marketing performance, just to name a few. Effectively collecting, analysing and actioning data has the potential to optimise all areas of e-commerce business from stock and fulfilment to digital merchandising and customer experience. Data can tell you who to market to and how, what pricing strategies are optimum and key dates in the customer lifecycle. As well as highlighting the best approaches, it can help you identify what isn’t working so well in order to enhance performance and processes.
Heightened by increased customer demand and the supply chain issues that spawned out of the pandemic, customer frustration about out of stock products has shifted from in-store to online. As of this, customers want to know that an item is in stock before ordering and if not, how long they can expect to wait for it. Real-time inventory management is a way to provide this information but many companies may require an upgrade to their existing data platform. From a fulfilment perspective, data is the key to keeping customers in the loop with their order progress in a way that can even help drive customer loyalty.
Customers are known to spend more in store than online, with organic physical browsing experiences encouraging 12% more impulse purchases, which in turn increases the average order value; sales which online retailers are missing out on since the majority of in-store shopping has shifted to online. Digital merchandising aims to close this gap, but utilising data analytics may help to do so more quickly by using customer and inventory insights to encourage sales, for example by promoting in-stock products customers are likely to want or by bundling slower selling items with more popular ones.
These are just some of the ways that data can be leveraged to improve business performance but in short, the application of data analytics helps companies become much more intelligent, making predictions and implementing actions based on insight rather than impressions. Rituals turned to Dept to help predict the behaviour of its customers in order to maximise sales. We used machine learning to predict conversion intent by matching real-time browsing behaviour to historical conversion patterns, resulting in much more efficient retargeting by honing in on audiences based on their expected probability to convert. This approach saved 40% of Rituals’ re-marketing ad spend without reducing conversions.
At the core of data-driven e-commerce marketing strategies is an understanding of the customer. This needs to extend much further beyond basic personal information to include the kinds of products they often browse, their interests, what they care about and any brand preferences they may have.
This data is found in multiple sources, such as the CRM, in-store POS systems, social media and app usage insights, and as a result, is often reviewed in silos. To combat this, a good first move can be to implement a customer data platform to better aggregate and analyse customer data from various sources and gain a single view of the customer.
Analysing data from all touchpoints and channels enables companies to gain a richer and smarter view of customer trends, which after applying machine learning, they can use to develop truly targeted campaigns; making sure the right products are put in front of customers at the right time to drive sales.
A data-fuelled strategy will look different for every company, depending on the type of business and products sold, its data maturity and its objectives. While becoming truly ‘data-driven’ (where data governs strategy and all business decisions are rooted in data insights) is an ambitious goal to aim for, it should not be the immediate area of focus for the majority of businesses.
The first step should be to understand your company’s data maturity and what stage it’s currently at in its data journey. Is it data challenged, aware or influenced? If you need help answering this question, Dept can help.
We can also assist you in understanding, unifying, analysing and activating your data to improve the bottom line. Get in touch with our experts to find out how we can help you launch or optimise your data strategy.