What can we learn from last year’s performance?

Last year’s holiday sale season was a good one for e-tailers, but a bit more mixed for traditional retailers. Now that AI is becoming more popular — and much more available, thanks to AI platforms and AI-based products — how can retailers utilize it? Specifically, how can AI make seasonal sales more successful?

4 Ways AI Boosts Seasonal Sales

First, let’s discuss a trend in data analytics: the movement towards intelligent analysis rather than simple data collection. We’re all aware that there is a lot of data available and that companies can use it to create accurate personas and micro-segments. We’re already seeing retailers take the logical extension of this fact and use this information to shape new products, ideas, and offers. But we can use AI to go one step further: to help us build winning strategies. Below are four areas where AI can be used to great effect:

  1. Matching Consumers with Products— Marketers often look for customers who have identified a problem/need/want, but who are not aware of all that’s available. To successfully market to this audience, customer data and product data must meet. High-quality product data — specifically, product attributes and purchase contexts — is essential if you want to make the best match between product and need. In turn, this can be combined with individual and aggregated customer data to create very specific and very effective offers (i.e. selecting not just the most appropriate product and incentive, but also the best outreach channel and time).
  2. Creating a Unified User Experience— Customers don’t stay neatly in one area: they shop at both physical stores and online shops; they interact with multiple departments (customer service, marketing, etc.); they use all kinds of devices to access a huge variety of channels, and they expect their experience between all these facets to be seamless. This requires a huge amount of concentrated effort on the part of the retailer. This starts with data, which must be shared across all relevant departments. It also requires internal coordination, like not marketing products that are unavailable in a customer’s location.
  3. Building Persona-Specific Branding— It’s not much of an exaggeration to say that companies live or die by the success of their branding. The trend today is towards hyperpersonalization, and consumers expect to see brand messaging that’s tailored to them. But how can companies achieve this? By using AI to understand customer micro-segments. In this way, retailers can address the exact needs of each consumer and build a one-to-one relationship between brand and customer.
  4. Optimizing Operations— AI can also be applied internally, to help retailers understand the best way of meeting their own needs with the resources available to them. A key example here is demand forecasting. An accurate demand forecast can reduce waste from buying too much material and overproducing a product. It can help retailers avoid underproducing an item and facing an out-of-stock situation. It can influence how companies manage their supply lines, logistics, shipping, delivery, and fulfillment. Once again, the more data retailers put into their internal analytics, the better the results.

Artificial Intelligence is not a cure-all during the holiday shopping season or at any other time. But it certainly can help retailers meet their goals while creating a very positive experience for their customers.

Authored by: Richa Kapoor, Manager at Absolutdata Analytics and Promita Majumdar, Marketing at Absolutdata Analytics


Related Absolutdata products and services:  AI and Data Sciences, Marketing Analytics, Customer Analytics, Retail, CPG