Push based, predictive customer support

During our last trip to India, soon after we boarded the 16 hour flight from SFO to Dubai and started settling kids, our 2-year old daughter started becoming uneasy. Watching us, one of flight attendants walked up to us and offered to bring hot water to prepare formula for the baby. This was a simple gesture, but saved us time and effort in figuring out the baby was hungry, calling for help, and then requesting for water when attendants are busy preparing for takeoff. The attendant, knowingly or unknowingly, predicted our need and fulfilled it proactively. Is it possible to build systems and processes that will allow companies to provide such proactive support in order to delight customers and reduce support costs?

In many situations, a customer’s first real touch point with a company starts when a customer contacts the company with an issue using e-mail, phone or chat, especially when the product is purchased online, through purchasing agents, or distributors. A push based support strategy seeks to engage customers even before a customer realizes he or she has a problem.

A simple example of a proactive strategy is a well-designed customer onboarding process. Whereas a reactive process waits for a customer to start using a product and run into issues, a proactive process will send relevant product information to the customer in advance, so customers have a great experience using the product. Such proactive approach requires companies to reach customers exactly at the right time and place when they need support in a non-intrusive way. While defensive support requires arming support teams with production information and troubleshooting tools, a push based approach requires careful planning, a detailed understanding of customer types, and adoption enabling technologies.

Push based customer support is analogous to behavioral ad targeting. An effective targeting strategy requires thorough understanding of target customers, collection of behavioral data, and reliable targeting technology. Going on the offensive with push based customer support also requires precise understanding of customers and what they do, data collection, predictive analytics, and effective support delivery methods.

One of the key elements of proactive support is a precise model of each type of customer and their workflows. For example, a Life Sciences company needs to have full understanding of what a cancer researcher does at a university lab. Currently, this level of customer knowledge is scattered throughout the company in the heads of engineers, sales reps, and support teams.

Once the model is in place, a profile needs to be generated for each customer, based on data from customer touch points, product purchases, and past support history. In many companies, CRM is viewed as the ultimate customer profile database, but for proactive support, a more real-time database is required. In addition to capturing the company’s view of customers, the database should allow customers to specify their own needs and preferences.

Analyzing customer behavioral data, product purchases, and support history can help predict potential short-term and long-term customer issues and needs. This is akin to a sales rep or account manager using her knowledge of a customer and customer’s product use to proactively offer help on certain aspects of the product or customer workflow.