In the past two years, human beings have produced more data than ever before in the history of our species. This has led to a data revolution in business. Data scientists have become the most coveted professionals in a wide range of industries, from finance to healthcare. Despite this, most of them spend the majority of their time manipulating data to turn it into a usable form, rather than extracting actionable business insights from it. The sheer volume and diversity of data is making it increasingly difficult for companies to extract real value, insights and decisions from it. Take companies in retail, for instance. In the past, merchants would push simply products into shops, put some billboards up, purchase a few spreads on popular magazines and watch customers filter into their stores. The internet has completely toppled this model. Nowadays, customers search for products online. They have the ability to compare pricing and features and read recommendations from peers. Retailers need to get to know their customers before they can start marketing to them. They need to know what they like, what they’re buying, when they shop, how their peers influence their shopping patterns…the list gets more complex by the day. In order for retailers to capitalize on this data, they need to find effective ways to collect it, manage it and analyze it.
How are retailers coping?
While big data is certainly posing challenges for retailers, opportunities still exist. Companies are experimenting with different models and basing their decision-making on testing rather than on intuition. One popular trend is using customer data for tailored services and promotions. Dutch supermarket chain Albert Heijn, for example, introduced new customer loyalty cards in October of last year to tailor special offers according to their customers’ purchasing behavior. The cards are anonymous by default, but thanks to the new loyalty program, shoppers will be able to activate their card online in order to build their user profile and get targeted product recommendations. Albert Heijn is also taking this one step further by releasing apps where shoppers can look for recipes, create a shopping list and find their way across the shop, paving the way for increased customer engagement and a wider understanding of their target audience.
Besides testing opportunities in personalized marketing, retailers are experimenting with dynamic pricing to maximize revenues from their merchandise. Airlines and hotel rental companies have used dynamic pricing technology for years and now savvy retailers are using it to offer the right price to the right customer at the right time. Companies like Zara, for instance, have started using Markdown Optimization to increase the efficiency of markdowns and focus on revenues instead of close out sales. This approach earned them a 6% increase in clearance revenues. The idea behind this dynamic pricing approach is to forgo fixed prices in exchange for prices that change in response to purchasing trends, market changes or noteworthy events. To be precise, dynamic pricing exploits the customer’s willingness to pay. Safeway and Amazon were some of the first American companies to experiment with this model. Media Markt, a leading consumer electronics retailer of German origin, has been one of its pioneers in Europe, drawing data from their competitors’pricing to adapt their own.
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Media mix optimization is another marketing analytics practice that is gaining popularity among retailers. And it should come as no surprise, the online marketing space is becoming increasingly crowded and complex. Which online marketing channel delivers the highest conversion rates? What is the best way to use Google Adwords? How can I best target customers online? Media mix optimization can help you answer these questions and support your media planning and buying decisions to maximize ROI.
Now this sounds great, but what does big data spell for the retail supply chain?
Dynamic pricing, media mix optimization, business model personalization…all of these data-driven initiatives can significantly impact your bottom line but they also have a dramatic effect on the retail supply chain. The pace of innovation, the innovation cycle and the time to market is frantic. It is therefore extremely important to have highly adaptable and agile operations when you’re taking data-driven decisions. This calls for a departure from “silo thinking.”You need to embrace “chain-wide thinking and actions,”as Professor Gino Van Ossel describes.
What can you do to start using data intelligently?
As the cases discussed above illustrate, marketing analytics is key not only to thrive but to survive in today’s fast changing retail ecosystem. If you’re looking to improve your analytics, there are a number of steps you can take:
- Start by defining your organization’s analytical maturity – what data are you currently collecting and how are you currently using it?
- Identify where you want to be in 2-3 years
- Build a strategy to achieve your analytical maturity with the right technology, partners, processes and structure in mind