It’s 2018. What’s the most revolutionary development in fashion over the past few years? Is it the check and plaid mania? Or maybe the shirtdress or the oversized, lightweight dress? Maybe it’s the apron and baby doll dresses that have entered the summer wardrobe (from the Halloween wardrobe)? The real answer to that question is data or much rather, the explosion of data that fashion houses are exposed to and the millions of ways that data can be interpreted and acted upon over the last few years. Shoppers these days are connected all the time, mobile ubiquity provides them the freedom to browse, research and shop where they want. You no longer need a customer to fill out a survey post their purchase, at a store, to understand who they are or what they like. You are now able to effectively build a profile of a customer using third party data sources like Instagram likes, for example, and get a pretty good understanding of their lifestyle before marketing to them.
If you looked at the fashion landscape and who’s really making the moolah, names like Amazon crops up. This is not right? They are not blue blood fashion retailer? Yet they are able to sell more fashion products than almost 40% of fashion retailers put together? They don’t have Giorgio Armani or a Coco Chanel suggesting what is the right outfit for every single customer? They don’t have a celebrity makeover team that is suggesting what color top a mother needs to wear to a soccer game? What they are good at is collecting data, deriving insights out of that data and acting on that data by putting the right product in front of the customer, at the right time, on the right channel.
You would assume that in this day and age, with all the power that data brings, increasing traffic to the store and getting customers to buy online should be fairly simple. Not really. The top challenges that fashion retailers are facing today when it comes increasing traffic are similar across the board and can be categorized into four main buckets:
- They don’t understand the customer and what interests them. They are simply unable to the catch signals online and off.
- Their customers don’t get context-aware, personalized communications.
- They are not giving enough reasons for the customer to keep coming back. Their loyalty campaigns are limited to a quarterly newsletter blast for example.
- They are unable to identify when a customer is ready to buy and lure them with offers that might attract that specific microsegment of customers.
To overcome these challenges the basic investment that’s needed for a fashion business is a Customer Data Platform (CDP) that gathers information from various sources like POS Systems, Online activity, Loyalty programs, CRM systems, third party data sources, etc. Once you have that in place, here are 5 ways you can exploit the insights and predictions to increase traffic to your store (online and off).
- Customer Life-cycle Marketing – Get the basics sorted. Create segments that you can use to put a label on every one of your current/ past customers. This could be based on where the customer is in their relationship with the brand, for example: just acquired, first-purchase, repeat buyer, loyal, wavering, churn.
- Micro-segmentation – Basic segments alone are not enough in the age of data. You need effective customer micro-segmentation based on lifestyle, life stage, behavioral, demographic and campaign responses to have an accurate view and understanding of each cluster. This would help you create highly relevant lists to run specific campaigns. There are some strong products out there that can help you do this using propensity modeling. You can forecast the future value of customer, rank and prioritize the customers and even allocate marketing budget using these advanced technologies. Make use of them.
- Effectively recommend the next-best offer – You can do this based on affinity between categories, brands and customer segments. For example, if over 40% of 30+ women bought a silver color sunglass with white oversized shirts, that’s a good indication for the system to throw up that insight to you or automatically recommend the silver glasses as a ‘complete the look’ recommendation online. If you can get a software that can identify cross-sell opportunities, personalize content/apps based on stage automatically using AI, even better.
- Path-to-purchase – NPS (Net Promoter Score) is not just a fancy word thrown around in the boardroom. It really does make sense, in every business. Identifying every customer segment’s journey/ path to purchase and chalking out all the touchpoints that led to a purchase is a key element of increasing traffic. Not only can it help you shorten the buyer’s journey but can help optimize marketing spend as well. Win-Win.
- Churn management – The last hat tip is to effectively manage the customers that are about to or have churned. The lazy approach, taken by most fashion businesses, unfortunately, is to include them in a newsletter group that regularly gets updates on a sale or some branding comm. At this stage, the business has effectively given up on these customers in my opinion. The first step to effective churn management is to identify customers that are likely to churn based on visit history, purchase/ lack of, campaign response and overall engagement. You can then build rules and logic to entice them with offers and promotions that are most relevant to their micro-segment, and in today’s world, these can be done automatically by the machine!