BANU DAL | COO
Competition has always been a challenge, getting tougher every day. No secret that a business outstrips the rivals, only when the customers are satisfied and engaged. As Peter Drucker put beautifully; “The purpose of a business is to create a customer.”
To claim customer engagement, there should be customers, coming back over and over again, to purchase the products or services. It is critical to know the customer and predict the behavior, to take any possible action. We have been told that CRM is the approach and Loyalty Program is the tool, but that was some decades ago.
I witness that this perception didn’t give any ground since I still hear retail professionals say “loyalty card is the way to collect the data and to know the customer”.
Oddly enough, the transaction logs conceal, so much more than the customers declare themselves, on a predesigned form.
I believe the reason behind the retailers’ assumption is, being stuck – for years – between RFM Segmentation with no reasonable action, campaigns sent out with bulk messaging and failure to personalize.
As technology advances and the processing power is more affordable, we – technology providers – can easily incorporate mathematical models in our software and deliver you high-performance solutions. It is not a myth anymore; You can know your customer, better than him or her. With “Data-driven Behavioral Segmentation”, it is possible to develop a new approach to enhance customer engagement.
I would like to take this occasion to update you on what we have been working on lately, regarding this new approach.
- With no doubt, the online and offline channels should be integrated. The transactions made in the physical store and the online purchases should be aggregated on a customer record. Although there is progress compared to the early days of multi-channel, the pain point I get to hear the most is that the retailers cannot trace the customer who is ‘identified with an email address while shopping online’ and is ‘recognized with the phone number in the store’. In pursuit of the omnichannel, the retailers are having a hard time deduplicating the channel customers. Applying the Detailer Deduplication model, we helped retailers overcome this hurdle.
- We depict the ideal customer and the behavior set, extract all the alike-unlike sets and customers from an ocean of data. Certainly, this is a tough job, however using the Big Data approach, we are able to analyze with high performance and accuracy.
- Without the hassle of inputting the variables regarding the sales dynamics, marketing strategies, we work on the T-Logs to deliver the correlations. We incorporate data mining methods to extract the rule sets. We shed light on the probability of selling Y to customers who bought X, the lift factor of X to the sale of product Z.
- Predefined segment structures that encapsulate the customers in “not so accurate” groups are no longer needed. The new approach is to segment the clientele solely on behavior; monetary scale, the composition of the basket/categories or the timing of the purchase – weekday, weekend, morning, between 14:00-15:00.
Let me wrap it up!
Don’t lose time with the data collected at the first encounter, declared by the customer, filled in the boxes of a form designed by the retailer, which is no longer up-to-date. Take time to evaluate the Big Data & Data Mining solutions and bother only to collect the email and phone number from the customers, for communication & easier deduplication purposes. Your data has millions of stories to tell.
If this is on your agenda, let’s have a chat!
Listen to your data, make intelligent decisions.