Are statistics the savior of modern retail? A few years ago, when big data became a mainstream concept, industry experts predicted it would enable quicker, closer, more relevant shopper interactions. Today, we still believe this… but we’re not necessarily that much closer to achieving it.
The retail sector has access to a vast amount of information. However, there’s a difference between having the numbers available to you, and delivering them in a manner that drives genuine customer insight.
At present, the majority of tier 1 retailers have some sort of investment – often outsourced – in business intelligence, and are receiving regular feedback, but the key metrics aren’t always being communicated to the right decision makers in an easily interpretable manner.
The issue becomes more pronounced when you move into tiers 2 and 3, as they have far fewer resources dedicated to BI. Often data monitoring is being run by an in-house IT team, which has far too many operational concerns to dedicate sufficient time and manpower to interpreting big data trends.
So how do retailers of all sizes start converting the vast ocean of information available to them into tangible improvements? It begins with understanding which metrics make the most difference to profit margin, and these tend to be:
- Customer buying patterns – in certain sectors in particular, such as luxury, it’s crucial to analyze which products are being bought in which months, weeks or even days, and which time or day customers are making purchases.
- Sales by demographic – it’s also important to identify which products sell well in certain channels or markets, and which customer groups are buying them. Understanding seasonal shifts in these patterns is a vital consideration, too.
- Product affinity – finally, correlations in customer behavior can add valuable profit-building opportunities. For example, if a customer is going to purchase a blue shirt, what is the likelihood they will also buy a purple tie?
By grasping these three metrics, retailers can begin to make some fundamental changes in the way they run their business. For instance, knowing who is purchasing what goods, where and when, can completely revolutionize the buying, allocation and replenishment cycle. It also enables retail decision makers to forecast sales based on demand.
Identifying correlations between products can have an additional positive impact on marketing, as retailers are able to target recommendations based on previous purchasing history – even running promotions on accessories they know perform well alongside certain items, to increase average basket values.
But extracting these metrics alone is not enough; they must be delivered to key personnel within a time frame, and in a way, that allows retailers to capitalize on new insights. Although, in the fast moving world of retail, senior staff simply don’t have the time to sift through streams of data and find trends.
To work around this, some businesses are deploying a business intelligence solution that features a dashboard, capable of extracting only the data streams relevant to each person’s role. This harnesses statistics from multiple channels in a single platform and delivers it in an easy-to-interpret format, enabling key decision makers to both see the bigger picture, and to act on it.
Additionally, these dashboards should be responsive across multiple devices, so that c-level decision makers such as merchandising and marketing can access them from any location on their mobile device, enabling them to carry out their jobs more effectively.
Making data analysis mobile-friendly closes the gap between theoretically being able to interpret trends, and having them delivered in the usable, real-time format that makes them actionable. Now it’s time for retailers to make the business intelligence solution investment that allows them to make the same leap.