Are you Using Customer Service Data Wisely?

I was recently speaking to a colleague about his email winback acquisition campaign and the flaming responses it generated. Although the creative and offer were compelling, his team had not segmented nor suppressed former customers with negative customer service history. As a result, some of these former customers called to complain, wrote emails to senior executives, and made their feelings known across social media.

Digging a litter deeper he confessed that the company’s customer service data was unstructured and in various locations. All of which made it hard extract, analyze, and append to the customer data used in the campaign.

I empathize with his plight.

Many of the organizations that I’ve worked with over the years have siloed data warehouses with unstructured customer service data. When faced with this situation, you can either take your chances (like my colleague) or at the very least, try to get customer service data that has the most impact on your results.

1) Positive or negative flag from the last transaction

2) NPS score from last transaction

3) Cancellation disposition codes

4) Customer service contact frequency

5) Return rate of goods sold

6) Online reviews and social media activity

The goal is to get “good enough” customer level data that allows you to identify, segment, and suppress “screamers” and other disgruntled former customers. Thinking about it from the customer’s POV is always the best place to start. Would you want to receive an invitation to “come back” when your last experience was below expectations or worse?

#data #customerservice