Insight-Driven Retail: The 3 Must-Knows for Retailers
In 2018, Forrester identified a new breed of fast-growing companies known as “insight-driven businesses.” Set to grow at a rate of 30% year-over-year, “insight-driven businesses” heavily invest in technologies that allow them to collect and analyze insights — specifically related to customer behavior and market trends — so that they can gain an edge over their competitors. This approach applies directly to retail and the modern way retailers price their products.
Each day, retail pricing is becoming more and more scientific with retailers leveraging precise analyses of rich, complex datasets to identify the correct prices for goods, services, and other value drivers such as branding. However, while adopting such a forward-thinking, analytic pricing strategy can have significant business impact, there are several areas that retailers need to keep top of mind when it comes to collecting data and preparing it for analysis.
Here are three of those key areas.
Identifying the Desired Result First
Having so much data can be exciting. However, if you don’t know exactly what you are trying to find out, you are likely to end up with partial, incomplete, or entirely useless results. Therefore, whether it is just one-off sales research or establishing evolving models for customer buying patterns, retailers need to think about what focus areas they are trying to find insights on before diving in. From there, everything else can fall into place.
Finding and Fixing Existing Internal Limitations
Enterprise IT infrastructures are usually designed primarily to manage a retailer’s internal data — such as customer databases, sales forecasts, and more — as efficiently as possible. Unfortunately, many retailers do not have enough flexibility in their infrastructures to cope with the ongoing deluge of data they are collecting or soon will be collecting. Moreover, they do not have proper tools to exclude outdated, unnecessary data in a timely enough way to get to the data they need. These limitations paired with the added complexities of pulling in external competitor data can prove to be very challenging for retailers that are not prepared for the volume of data that they will have on their plates.
Refining Data for Decisions
Once internal data infrastructure has been optimized, retailers need to make sure they have the proper talent and tools in place to collect and process data from multiple sources and refine it to meet the needs of a specific project and derive the desired results. Ensuring that data can be used to deliver a detailed analysis includes:
- Choosing the best sources and collecting the data that is relevant to the use case and the current business goals;
- Unifying and classifying data so that products can be found easily and their prices adjusted as simply as possible;
- Prepping and cleaning the data for the next phase of analysis.
Each task has its own unique nuances, so having the team in place to do the job correctly is incredibly important.
Retail and pricing are in the midst of a data revolution. By embracing the proper tools and having a well thought-out strategy, retailers will be able to deliver better pricing results and boost revenue in a way they never have before.