Do you remember when shopping online was far from being the hassle-free experience it is today? Up until the early 2000s, connecting to the web made an odd crackling sound, loading pages could take up to several minutes, and having access to the Internet at home was a luxury that many people could not afford. Fast-forward to today: shopping online has never been more fun and convenient, and can be done from the palm of your hand, anywhere, and at any time. However, what may seem like an easy process to the consumer actually requires a very well-thought-out and perfectly executed omni-channel strategy on the retailer’s side. What’s more, the mobilization of retail and a renewed focus on customer centricity requires a holistic real-time view of the customer and seamless, frictionless customer experiences. So, how can retailers better understand, influence, and manage the customer’s journey using retail analytics? Here are three easy steps retailers can follow to succeed.
1. Know your customer across channels
Retailers can get a better understanding of who their online customers are if they monitor visits, site interaction views, abandoned carts, recommended products, wish lists/favorites, etc. What’s more, based on in-store interactions, such as visits, views, notes, preferences, recommended products, retailers have a wealth of information they can track. Combining customers’ online and in-store profiles is, therefore, key to maintaining good relationships with them. While most retailers use analytics for e-commerce or basic retail operations today, many of them still fail at gathering data and sharing it across channels and organizational silos.
It’s equally important to know who your cross-channel shoppers are, as they typically spend more, are more loyal, and are more likely to recommend your store to others, than single-channel shoppers. According to HBR, consumers who shop across channels, rather than a single channel, spend up to four times as much as single-channel shoppers.
2. Use data to drive recommendations, promotions, and interactions across all channels
Retailers should use tools that can generate targeted and personalized messaging and offers to create a unique and memorable customer experience. According to Retail Dive, 83% of retailers will use suggestive selling based on previous purchases within three years. However, retailers should not solely rely on suggestive selling if they wish to set themselves apart. Using past purchases along with sophisticated algorithms can help them identify similar types of customers. In fact, customer segmentation can prove particularly useful when it comes to knowing what will resonate with a particular audience.
To drive customer loyalty and build meaningful relationships with customers, retailers should consider offering personalized promotions and data-driven customer loyalty programs. Using a strategy of near real-time and historical intelligence alongside retail analytics can also empower retailers with inventory insights by item, attribute, and market as well as predictive price modeling allowing for the discovery of pricing price trends and the propensity of competitors to adjust prices for price-sensitive products.
3. Build learning models to improve each subsequent interaction
Machine learning is the key to creating an outstanding customer experience, as the more retailers interact with a customer, the smarter their recommendations get. Learning models can come in a number of different forms, such as uplift modeling, propensity modeling, CLV, clustering, affinity, and collaborative filtering. Lifecycle modeling, for example, can help retailers know where their customers are in the lifecycle. Data-driven marketing can triple conservation rates, while customer segmentation can lower unsubscribe rates by 28%. This results in better engagement, increased open rates, click-through rates, and conversion rates. The use and gathering of rich customer data help associates better engage with customers, and to enrich and enhance the customer profile for better future engagements.
Knowing a customer across channels allows for features that exist in e-commerce to become even more effective through a better understanding of the customer as soon as they register an account. When they register online, their experience synchronizes with the in-store experience. What they see, what offers or promotions are provided, and personalized recommendations are all influenced by a unified view. Even more so is the ability to encourage the customer to engage across channels, through tools that can provide highly curated pages based on in-store and on-line consolidation of data, and shared wish lists, preferences and surveys, and much more. Retailers should be encouraging associates to drive business online, and need to put into place the business process to compensate associates for such actions. Store associates often see e-commerce as competition, so retailers need tools to enable associates to build a basket and push it to a customer to buy it online. Getting omni-channel retailing right may not be easy, but the retailers who use data to their advantage can drive more sales, enhance the customer experience, and create meaningful long-lasting relationships with customers.
