Winning Customers with Retail Business Analytics

Retailers have faced the substantial challenge of drawing customers in and keeping them on board since the very beginnings of the industry. And in today’s hyper-connected, omnichannel retail landscape, customer acquisition and retention have never had so much potential to make or break any merchant’s bottom line. Retail Business Analytics is one major force completely transforming how retailers go about attracting and retaining customers. According to Markets and Markets, the worldwide market size for retail analytics is predicted to grow from $4.3 billion in 2020 to more than $11 billion by 2025.

Which aspects of retail business analytics are driving this growth of more than 21 percent annually? Data visualization, the ever-growing pool of data available for analysis and enterprises’ rising cloud adoption — to name a few.

Here’s a closer look at how companies are harnessing retail business analytic to win customers.

Anticipating Customers’ Wants and Needs

Marketing has always been a matter of attempting to strike while the iron is hot, of course. But the timeframe for reaching customers with relevant messaging is getting narrower as consumers increasingly demand speedier, more convenient and more seamless experiences with brands — and give their business to companies able to deliver.

As Harvard Business Review notes, modern analytics helps retailers take advantage of “increasingly granular data” — like in-depth demographics, psychographics and consumer behavior across channels — to create highly customized “next best offers.”

Analytics platforms help take this personalization to the next level by enabling smooth, speedy data analysis across millions or billions of data rows from many different sources. Access to self-service analytics in particular allows marketers to ask important customer-focused questions from data so they can tailor their campaigns. Furthermore, AI-driven analytics can mine those vast data stores for interesting patterns or anomalies and notify relevant teams so they can act upon these insights.

Retailers best able to take advantage of customer data to anticipate buyers’ wants and needs — then reach them at the optimal time through the most relevant channel — will gain a competitive edge in terms of acquisition and retention.

Breaking Down Data Silos to Improve Insights

A difficulty retail organizations have traditionally faced, despite the growing volume of available data is silos — that is, separations in terms of how data is stored and who has access to which data sources.

An example of a siloed organization might look like the IT team having the best insights on ecommerce website usability, marketers having insights on conversion rates, merchandisers having access to SKU and product recall data and customer service teams having access to granular data regarding returns and complaints. Another way customer data may be siloed is by channel and source — with social media data, website data, point-of-sale data and more residing separately, making it difficult to access and get a 360-degree view.

Contemporary data platforms democratize data, making it accessible to the widest possible user base across a company. While administrators still control who sees which insights and to protect sensitive information, front-facing analytics tools open a wide array of insights to a broader variety of users. This means employees who make key decisions in setting and optimizing customer strategy from start to finish can quickly access the insights they need without jumping through hoops.

Part of bringing down cumbersome siloes is empowering employees to retrieve their own data insights on an as-needed basis rather than having to wait for reports. This reduces bottlenecks and wait times so employees can act quickly as the context demands.

Winning customers over may not be easy these days, but retail analytics help companies understand their buyers and serve them well.