Big Data might seem like it’s primarily a numbers-crunching activity, and one that is primarily geared to marketing. That couldn’t be further from the truth: data analytics can be applied at nearly any point in the business work flow, and in any area.
Take in-store customer behavior. As a previous post pointed out, Big Data can not only help retailers understand their customers, it can also show them how to improve customers’ in-store experience (and get more sales).
Big Data is now being applied to every part of the retail process, by online and offline businesses of all sizes. In this post, we’ll briefly consider how you can use Big Data to:
- Predict Trends and Forecast Demand
- Optimize Prices
- Target Customers
- Identify the Next Likely Purchase
- Increase Customer Engagement and Boost ROI
Let’s dive in.
Predicting Trends and Forecasting Demand
Predicting trends is rarely easy: to do it successfully involves putting together a diverse array of behavior patterns, cultural leanings, potential impacts, and historical data. However, with Big Data analytics on your side, these patterns become easier to isolate.
Once the ‘Next Big Thing’ has been identified, companies can begin fine tuning how they will meet the demand for it. Once again, a lot of information goes into this process; geographic and climate data, demographics, even regional preferences and overall spending habits come into play. When trend prediction and demand forecasting are done properly, they enable retailers to get the right products to the right areas at the right time. They can also help companies avoid a costly surplus of unwanted (and later deeply discounted) goods.
Markets change quickly. Fortunately, Big Data analytics can monitor these changes as they happen. This gives retailers a window into the complete market picture, from local weather to competitor activity. Based on this input, informed decisions can be made about raising or lowering prices in accord with demand, not merely as tradition suggest (i.e. marking down sandals at the end of summer).
Customers create large amounts of data. According to Big Data Made Simple, this can come through lots of channels, including in-store CCTV footage, Internet usage (especially when connected to a store’s Wi-Fi), social media accounts, membership or loyalty cards, and retailers’ own transactional records. Putting all this data to use allows companies to create personalized campaigns that are much more effective at persuading customers.
Knowing customers as individuals means knowing their preferences and what offers will get their attention. Today, retailers can digitally send coupons and special offers to their customers while the latter are actually shopping in the store. Such offers can appear via text message or a push notification from the retailer’s mobile app – or even at the checkout. This kind of attention can’t be done through the mail or a TV ad; it’s got to be done on the spot.
Identifying the Next Likely Purchase
Once again, Big Data gets personal. Not only can it enable granular customer segmentation, it can uncover those same hidden patterns we talked about in spotting new trends – but on an individual level. By tailoring offers to a 360-degree view of the customer, it increases the chances of successful conversion. Could this lead to a change in marketing itself – a movement away from mass marketing and towards personal messages? Possibly.
Increasing Customer Engagement and Boosting ROI
What does all this personalized attention add up to? Happy, loyal customers. By keeping customer interests and preferences at the center of marketing campaigns (and your social media efforts), you are in a much better position to meet customer needs. This has a kind of positive domino effect, ultimately creating better returns for your budgetary buck.
The long and short of the matter is that now is the time for all retailers to start getting serious about using Big Data analytics. Customers are telling you what they want through multiple channels. Industry data and your company’s own records contain a mine of potential insights that are waiting to be unlocked. Do that, and you’ll be able to harness the potential of Big Data across every aspect of your business.