As data analysis helps to improve technical support Zapier

As data analysis helps to improve technical support Zapier

SHARE

Title startup Zapier may not be at the hearing, but the authors make an interesting and necessary thing – a web service that allows you to interconnect other services. In many ways this is an analogue of an earlier IFTTT, but first, where would lshim choice of sources (and receivers) information and, secondly, with the corporate bias. From Zapier, for example, you can automatically save attachments from Gmail to Dropbox, and can be integrated with each other Salesforce, Asana, Zendesk, Mailchimp and other popular solutions.

Altogether Zapier about 150,000 customers who use more than 600 thousand integrations between services. Large-scale studies based on “big data” – daily routine specialists Zapier, and these studies involve all aspects of the company. In particular, the official blog Zapier engineer Mick Bennett talks about how “big data” to help the company improve technical support.

When Bennett joined the team Zapier autumn 2012, no one kept statistics on the volume and performance of technical support. The company from time to time to view reports that were generated Help Scout (software technical support), but all these charts and graphs did not bring any benefit.

data-analysis-helps-improve-technical-support-zapier-wovow.org-02

By the end of the year it became apparent that the company needs a systematic approach to decision making. Thus was born the Support Recap – document in Google Drive, which collected and permanently stored templates of reports information Help Scout. The appearance of such documents resumes great benefit and influenced the course of several major initiatives launched by the team Zapier.

In the middle of last year Zapier seen steady growth in technical support work. Although the company suspected something like seeing a compelling and sometimes shocking figures, they began to address the problem. The whole team for a week sat down to write a manual on 278 pages from scratch. Those summaries allowed the company to assess what made the right decision, because the number of requests to technical support after the publication of the guide immediately sank.

The next step to improve the assessment of technical support is amazingly simple solution – to find out how satisfied customers. At the end of 2012 in Zapier implemented Hively – Services to help interview clients. Use it for signatures at the end of emails a link to the form of performance evaluation Ticket. Feedback form in every letter, every step of the interaction, not just at the close of the ticket. As in the previous case, the company on the basis of numbers confirmed their suspicions that the customers are satisfied with the service.

In early 2014 decided to again revise Zapier Support Recap. Now most correspondence (ie chains of e-mails in the inbox Ticket) when reporting is given less importance. It turned out that the amount of correspondence, as the basic unit of measurement of the volume of technical support, confusing and make noise in the calculations. The company still tracks the number of emails, but it is no longer important parameter estimates.

In tech support Zapier started attaching much more important role of time between request and response: This option helps to effectively measure the amount of work. Obviously, to correspond with ten answers spent more manpower than one. The company is interested in providing people with solutions to technical problems and thus meet the fewest number of letters. Number of responses in combination with the “closed bugs” in Help Scout helps measure both.

Team happy with improvements made over the past year, but, of course, there is always a new challenge – especially if there are at hand the necessary data.

Now Help Scout provides summarize information that gives a holistic picture. In the future, want to realize Zapier detail on temporary basis. This will not only watch the performance schedule for the day, but also keep track of calls made outside these hours. At the same time it will be possible to solve the problem of requests received during the day on weekdays – when customers due to busy to wait for technical support response is particularly long.

Hively data also will be used more actively. It integrates with Help Scout, and evaluation data service customers, will be tied to the letters to support. This will specifically evaluate the feedback and act in accordance with this understanding. In general, customers now Zapier satisfied with the services provided, and the data will help in the future even more deeply explore the weaknesses that accompany negative customer reviews.

SHARE