The Impact Of Customer Analytics In The Age Of The Omnichannel Customer
Retail in the new decade is very different from what brands expected at the beginning of the new millennium. Armed with smartphones giving access to hundreds or thousands of apps for comparison, shopping, and exclusive deals, a typical customer today makes very informed buying decisions in an instant. Customer experience drives retail transactions. Businesses must strive to offer a consistent omnichannel experience to all customers in every channel they use.
Omnichannel retailing virtually displaces the thin line that existed between physical in-store shopping and the world of e-commerce. US shoppers alone spent a record USD 34.36 Billion on e-commerce websites over 5-days from Thanksgiving to Cyber Monday. The spike in spending online may have been due to the COVID 19 pandemic which largely affected in-store purchases. Nevertheless, brands and retailers have been trying to make the omnichannel experience rewarding for customers who look to buy their favorite goods at the most desirable prices and with greater convenience.
The key weapon they can rely on to create powerful omnichannel experiences is customer analytics. Retailers need to leverage analytics to drive the buyer journey forward as customers become more demanding in terms of the value they get for every dollar spent.
So, how does customer analytics help? Let us have a look at 4 areas where customer analytics can deliver a great impact in the age of omnichannel customer experience:
Personalize Every Interaction
Over the course of a shopping journey, customers may interact with different departments across a retail organization from sales to logistics, support, returns, finance, etc. to name a few. To offer a truly personalized experience for shoppers, it is important to analyze and identify the challenges in these interactions with each department and solve them. It is also
crucial to understand exactly how different customers interface with these different functions and for what purpose.
Deep analytics can help retailers to identify the key elements to focus on to deliver a personalized customer interaction. Some examples could be the right time to send a promotional email, the best products to be used for cross-selling or up-selling, the favorable budget or price range for a customer, the preferences the customer has for longer support services after purchase, etc. Only then will retailers be able to deliver unique customer experiences irrespective of the medium they use like mobiles, web browsers, or in-store purchases.
Unifies the Commerce Experience
Surveys have shown that nearly 85% of retailers prioritize the need to have a unified environment for shoppers. Irrespective of which medium they use to purchase items, they understand that the experience should be consistent. Retailers need to unify the experience so buyers can keep moving forward in the journey even as they switch devices and channels.
By using customer analytics, companies can also gain insights into what will engage customers at each stage and then use the same to simplify the journey. This journey stretches from supply chain to inventory and warehouse management to logistics. It covers pricing on all channels ranging from physical brand stores, multi-brand retail outlets, and online retail in both web and mobile platforms. Customer analytics helps companies to uncover hidden insights in each of these areas and this value can be translated into better and more personalized experiences across all interaction points with the customer to
create a consistent and unified model.
Enables Strategic Marketing
Customer analytics enables retailers to learn more about what customers need and how they plan to go about procuring the same. This insight can fuel data-driven targeted marketing campaigns and initiatives that span channels and which have a higher chance of converting. In an omnichannel environment, brands can leverage analytics to know what works well in-store and what works best online and then focus on creating marketing messages that deliver more value for shoppers relevant to their past actions and choices.
With analytics, it is possible to identify hot trends and scale-up campaign outreach across millions of interactions on the web and in physical stores.
As mentioned earlier, analytics enabled retailers to gain insights into previously hidden customer preferences. For example, a retailer might understand that customers research some specific items online but prefer to buy them in-store after a final inspection or trial. This insight can be used to ensure the availability of goods in stores based on an analysis of the search and content consumption trends in an area. Such strategies help prevent overstocking of items and control costs in the process and can even help in optimizing the supply chain to ensure the demands of all channels are optimally met. By running analytics on results from marketing activities, it becomes easier for brands to predict sales and demand from different channels and fine-tune their efforts to provide customers with their desired experiences for every interaction.
As digital transformation takes root across the retail landscape, retailers have the opportunity to tap into data from different sources that tells them more about their customer. For instance, earlier, a footwear retailer could only promote the desired brand to shoppers who they knew were interested in shoes. But today, the brands have a much more nuanced view of the customer. Based on analysis of their online behavior and by tapping into the information available from other channels such as the number of steps he or she makes in a day, brands can create specific product bundles that are exactly right for them.
Data is available. It’s now up to analytics to play a larger role in helping brands establish a better relationship with customers by driven more concerted strategies that account for the omnichannel customer.