Customer Signals: Understanding Onsite Search Analytics

The world is generating more than 2.5 billion gigabytes of data every day, with 80% of that data considered “unstructured” content such as customer interactions. The obvious challenge for organizations is extracting valuable insights from all of this data.

Companies that strive to provide an exceptional customer experience should take proactive measures to understand overall satisfaction throughout the customer journey, and then quickly take action to improve this experience based on the data.

Customer journey analytics (CJA) is the latest technology tool in customer care. However, it is no longer enough to just understand today’s customers, companies now must anticipate their needs and deliver throughout the journey.

Listening to Your Customers

Perhaps the strongest signal a customer can send is through an Onsite Search request. By monitoring customer behaviors and analyzing the type of questions asked, support teams can intelligently determine a range of user confusion and pain points.

Analyzing these searches provides deep insight into a customer’s intent. Knowledge Base managers can apply these learnings to develop and expand support content. Some examples of insights that search analysis might uncover include:

• How a Knowledge Base is being accessed by customers and agents;
• If the existing content is effective (is it accessible, easily comprehendible);
• What content is missing, outdated, or needs revising;
• If there are redundancies or overlapping answers;
• User Performance: the number of clicks, their origin, top content clicked on, ratio of questions, answers, and clicks over timelines; and
• Response times and efficiency of ticketing session requests.

Gaining a clear understanding of how FAQs are being used provides acute transparency into the customer experience. With the appropriate response, companies most often improve their Self-Service ratio which ultimately increases case or ticket deflection. Search learnings can also lead to better marketing strategies and can even help increase the rate of sales conversions.

Case in Point

With the help of Inbenta’s cloud-based customer dashboard, Backstage, Farmgirl Flowers accessed deep insight into how its customers were interacting with customer support. The company was able to ascertain that twice the amount of people were searching for answers than it thought. Turns out that instead of contacting customer support for their answer, a sizable number of customers were giving up on finding the information they wanted and most likely leaving the website.

Furthermore, with a Natural Language Processing semantic clustering tool, Farmgirl Flowers was able to further perfect its Knowledge Base. By understanding the different ways people were asking for the same answer, it was able to ensure that every question—despite the language used—had a relevant response.

Improving customer online self-service support proved to be a critical decision for this growing company. Because Farmgirl Flowers’ customers now had easy access to the answers they were looking for, they were less likely to abandon their path to purchase. Shortly after implementing Inbenta, sales increased by 15%.

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If you’re interested in learning more about Onsite Search analytics and Inbenta’s Backstage technology, please visit www.Inbenta.com or email us at info@inbenta.com.