Exceptional customer experience is the foundation of every successful business. Companies that consistently improve and enhance their service develop trusting relationships with their customers. This opens the door for repeat orders, as well as upselling and cross-selling of their products. In the process, a strong recurring customer base strengthens and boosts their long-term bottom line.
According to a recent Tribridge report, one of the key ways to enrich this customer experience is informing strategies through data analysis. In our digital age, shoppers actually expect companies to use insights from their purchase history to tailor their buying experience. This includes creating custom messaging, offers and personalized incentives.
The Missing Puzzle Piece
In the current multi-channel marketplace, it is essential that you gain a comprehensive, 360-degree view of your customer data before taking action. Without doing so, it is impossible to accurately improve operational decision-making and truly tailor your customer service.
Yet with vast quantities of information pouring in, it can be difficult to understand where to draw data from and how to distill it into actionable insights.
Most distributors associate data solely with statistics pulled from digital sales channels, such as e-commerce. However, even in today’s mature distribution landscape, a massive 74 percent of customers still prefer to email their purchase orders. As a result, by only analyzing data from digital channels, a large and vital source of customer insight is neglected — unstructured data from the inside sales and customer service teams.
With emailed orders typically processed by hand, it would take months just to identify which incoming emails contained purchase orders. Gathering and developing insights that can be actionable or necessary to improve customer experience from this data point is subsequently a challenge. How then to gain the 360-degree view of customer data you need to inform key operational decisions?
Accessing the Full 360 View
Data analytics technology can help bridge the gap between manual order processing and a need for a comprehensive understanding of customer experience. Using a powerful data assessment engine, it can examine thousands of sales emails in minutes rather than months.
This is achieved through rapid, programmatic scanning of incoming emails to filter out purchase order attachments from other general correspondence. Once completed, the engine then applies an algorithm to analyze details from these orders, delivering valuable insight into customers, their habits and their purchasing needs.
Combined with the customer data drawn from channels like e-commerce or portals, distributors then have a complete view of customers across every sales channel. In this way, the distributor can clearly pinpoint customer sales trends to enhance customer experience and ultimately boost the bottom line.
Understanding Customer Purchase Patterns and Demand
Who is your customer? When do they shop and what do they buy? Knowing the answer to these key questions helps create concrete customer profiles that improve every aspect of business operations and planning, from marketing to sales to inventory control.
Take for example a concrete distributor. By collating and analyzing data points from all sales channels, they may discover that a certain key customer purchases a considerable bulk quantity of cement every year around the same period. By identifying this buying habit, they are presented with several lucrative opportunities. For example, the distributor can ensure adequate stock of inventory during this time to meet the customer’s demand. They can also create personalized and highly targeted offers for this customer to encourage an even larger purchase. Further still, leveraging this pattern, they can spotlight complementary concrete products, such as adhesives and concrete forming supplies, cross-selling these items at a time the distributor now knows the customer is most likely to be persuaded by sales strategies.
Visibility Across Customer Purchase Preferences
CSR efficiency and expertise are crucial to a positive customer experience. Customers do not want to wait hours on a customer service line only to receive little assistance when they finally get through. Understanding what time of day and where customers place their orders, be it by email, e-commerce or phone, helps companies more effectively allocate resources and provide customer support catered specifically to those needs.
For instance, examining your organization’s customer data can reveal that some customers prefer to order via your e-commerce system on Mondays and Fridays between 9 a.m. and noon. As a result, you can ensure a higher number of experienced digital CSRs are available to be contacted at these peak times to answer any questions they may have during the purchasing process. Customers leave happy and with a positive impression of your business while you gain sales and potential return buyers.
Insight into Your Customer Service Model
Every customer account is unique. Some prefer a hands-off approach while others require more nurturing from CSR staff. Data gathered from incoming purchase orders allows you to determine how much time your customer service team spends assisting each customer and which customers require the most effort to support. Senior leadership can then work to craft sales and service-related messaging specifically targeted towards each of these customers and their pain points to simplify the support process.
Ensuring Informed Business Decisions
Operational decisions are key to successfully adapting to today’s ever-evolving marketplace. Grounding them in empirical data will ensure correctly predicted pain points in the sales and CSR workflow before they negatively impact your business. It’s then possible to accurately prescribe appropriate solutions that generate genuine results and ROI. For example, if data analytics indicates an issue with order fulfilment due to error rates in manual processing, third party solutions can be considered, such as process automation, to reduce these errors and prevent erosion of customer relationships.
Ultimately, a happy customer is a return customer, and a return customer means recurring revenue. Ensuring high levels of customer satisfaction is a crucial priority for every distributor. Data analytics technology helps merge data insights from digital and human resource channels to develop a clear, 360-degree view of customer purchasing patterns. This includes when they prefer to shop, what they choose to buy, and the effort required to support their needs. In this way, you can craft a personalized and efficient service experience for each customer persona, setting your company apart with a competitive edge.
Earl van As is Vice President of Marketing & Product Management of ecmarket, cloud solutions developer of the patent-pending Conexiom sales order and invoice automation solution. Conexiom allows manufacturers and distributors to focus on serving customers and managing supplier relationships instead of entering data. For more information, visit conexiom.com.