The DataHero Blog

Connecting Customer Support Efforts To Sales

June 5th, 2014

Connecting Customer Support To Sales

We know that customer support is an important aspect of any business, contributing to customer satisfaction, retention, and most importantly, sales. By merging datasets from a customer support service and a CRM system, you can see how customer support responses contribute directly to sales efforts. Here are some best practices on how to leverage integrated customer support analytics with sales data for your fast-growing business.

The best way to combine datasets is by customer email or company. If you combine based on the individual who emailed your help desk , ensure this is the same contact you have in your CRM system.

Once the data is imported from your customer support service and your CRM system, combining the two datasets is a matter of a few drag and drop motions on a common key:

After the groundwork for data analysis is laid with the combined dataset, we’ll start making the charts that can connect revenue to support cases. DataHero automatically creates suggested charts based on patterns in each specific dataset, or you can create a new chart.

Now we’ll create a new chart so I can outline exactly which attributes to add to each chart to get the answers to your business questions.

Monitor Win/Loss Ratio by Response Time

The chart below depicts customer support response time by whether the deal was won or lost from the CRM system:

In this example, we can see that wins significantly decrease as the response time increases. This may point to a need for the support agents to respond as quickly as possible to prospective leads.

Follow A Company’s Relationship With Your Company

Integrating your support and sales data allows you to get the full picture on how your company is building a relationship with another company. The chart below shows tickets filed by company, but filtered for only won deals:

In the example above, we can see how a company like Acme corp had help tickets peak in March, then decline after that. This can also give valuable insight into how and when to follow up with customers after a deal is closed.

Cohort Analysis – Deal Close Date and Ticket Creation Date

Perform cohort analysis by dragging on two dates and seeing how much follow up each cohort requests:

The group of companies who closed deals in December are depicted in the blue, and as a group they filed about 30 tickets in January, then about 15 in February, none in March, and about 4 in April. This would suggest that for your deal follow-ups, it may make sense to reach out to companies you closed deals with once a month for the first few months.

With these charts that show us where to look, we can improve both the sales and customer support systems in place, to make better data-driven decisions that benefit your customer.   Get the answers you need  today by merging datasets more easily than ever before. Sign up for a DataHero account and give it a try with your data today.

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By Kelli Simpson

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