Push based customer support
In many situations, a customer’s first real touchpoint 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 a 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.
Implementing a push strategy
Push based customer support is analogous to behavioural ad targeting. An effective targeting strategy requires a thorough understanding of target customers, the collection of behavioural 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.
Precise understanding of customer workflows
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 a 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 touchpoints, 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 behavioural 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.
Rather than waiting for customers to initiate a request through phone or web, companies need to reach out to customers at the right place and time. With the ubiquitous nature of smartphones, personalized delivery of customer support material is relatively easy to implement. The need to deliver a unique experience might require the development of an app specifically for customer support.
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