Partner Voices: Turn Analytics Into Sales-Driving Merchandising Insights
The ability for merchants to use analytics and cognitive computing rather than instinct and "gut" feelings to make decisions can be the difference between a profitable business and one that's not going to be around for much longer. With real-time insights into consumer behaviors as well as business and product performance, online merchandisers are better able to the put the right product, message or offer in front of the right person in the right channel at the right time.
With the help of a cognitive assistant, online merchandisers can anticipate problems and identify trends impacting their business — e.g., a drop in a product’s sales due to an inventory shortage or competitor pricing — enabling them to go from insight to action to results quickly. That's a formula that boosts customer engagement and, more importantly, sales.
Cognitive systems can help practitioners make faster, better decisions that improve customer engagement, drive sales and improve loyalty.
For example, a shopper on a men’s apparel site looking at dress shirts can be presented with product options in his exact style (point collar, spread collar, button cuffs, French cuffs), size, color, fabric (cotton, man-made fabrics, silk) and pattern (solid, stripe, checked) based on factors such as his previous purchases, browsing behavior, search intent, and call-center or online chat interactions. And this personalization can be done in real time.
Furthermore, at the time the shopper is on the product page, he can be presented with personalized content (e.g., a style guide on matching shirts with neckties and suits), offers (e.g., a banner ad promoting a sale on the same brand and style of dress shirts that the customer has previously purchased) and messaging. This level of personalization — in real time — yields higher conversion rates and brand loyalty.
Merchandising on a Personal Level
The idea of merchants making product decisions based on what they feel customers want is no longer practical. Customers are constantly telling merchants what they want through their behaviors and purchases, whether it be in-store, online or through social channels. It’s therefore incumbent upon the retailer to present them with relevant products, messaging and offers.
Even with this significant amount of customer information, the practice of using real-time, actionable insights from customer data to drive merchandising decisions is far from commonplace. Retailers know they should be, and to some degree are, using analytics to make merchandising decisions. Most have more than enough data to do so. However, their inability to assemble, process and make sense of all that structured and unstructured data is preventing them from being more proficient at true insight-driven merchandising.
A recent IBM survey of 137 merchandising and e-commerce professionals revealed that 53 percent of respondents said they’re able to present some form of personalized products, offers and promotions, yet 63 percent also believe they need to improve analytics technology, automate data analysis, and make sure they have relevant data from all channels and functions inside and outside of their company. Furthermore, only 30 percent are very confident in their company’s ability to analyze customer data and develop accurate, valuable, actionable insights into how customers behave and shop within digital channels.
Speed is of the Essence
A lack of customer data isn’t the problem for retailers; in fact, too much of it may be the issue. With all of the different customer touchpoints — stores, online, social media, mobile apps, loyalty programs, call centers, etc. — brands are collecting more data about their customers than ever before. The key is being able to distill all that information down to what’s truly meaningful, and being able to do so in a timely manner so brands can take action. Automation makes that possible.
Thirty-five percent of respondents to IBM’s survey said they’re working to automate the analysis of customer, market and business performance data to extract insights and key findings that are actionable and help them improve customer engagement and drive sales. It seems this number should be higher, especially given the fact that 61 percent of respondents rated having analytics for insights into customer behavior in real time as very important.
As noted above, retailers want (and need) more from their merchandising analytics technology. Just 30 percent said the technology they’re currently using provides everything they need and more. From the management and maintenance of disparate databases to a lack of integration between systems to insufficient data analytics capabilities, technology challenges are preventing many retailers from winning customers in this hypercompetitive digital retail environment.
How Cognitive Can Help
With the problem identified, and the benefits of insight-driven merchandising clear, retailers are tasked with finding the right technology solution that can enable them to quickly take action on customer engagement opportunities. That’s where cognitive commerce — i.e., systems that learn at scale, reason with purpose and interact with humans naturally — can help.
Cognitive commerce can analyze an expanded set of structured and unstructured data, finding hidden connections and patterns that present opportunities to improve business performance. Those insights lead to recommended merchandising actions that have the highest probability of engaging shoppers in more personal and relevant ways.
Adopting cognitive commerce technologies can lead to many benefits, including:
- Better collection and aggregation of data, resulting in deeper insights into customer behavior, trends and business performance. The more you know about a customer, the better you’re able to sell to that customer.
- Time savings from no longer having to sift through data and reports from many unconnected systems.
- Better digital experiences for customers AND employees. Customers get more relevant products, messages and offers, while employees become more efficient, allowing them to think more strategically about their businesses.
- A return to a more personal customer–brand relationship. With all of these insights at their fingertips, store associates are more effective at providing service and engaging customers at a personal level. Cognitive sales associate tools offer an opportunity for brands to differentiate themselves while making in-store shopping as personal as it was 50 years ago.
- An improved bottom line (isn’t this what we’re all after?). Realize cost savings from reduced marketing spend — personalized and targeted vs. more quantity — and better inventory management, and sales gains from increased conversions and improved customer loyalty.
The path to a more profitable business starts with giving your customers the best experience possible every time they shop with you. That means using what you know about them — both implicitly and explicitly — to make decisions in real time that will best serve their wants and needs. That rings true whether it’s merchandising, marketing, fulfillment or any other part of your business. Use data and cognitive commerce as the foundation for customer loyalty.