Unstructured customer feedback in Salesforce

What is unstructured customer feedback?

Unstructured customer feedback is everywhere. As an avid Salesforce user you know the importance of creating a personalized customer experience. You know it involves time, resources and most importantly the right tools to reach customers and understand them on a deeper level. Of course, like anything in business, new methods and processes bring with them new obstacles. With the endless CRM tools available to us, we’ve become extremely skilled at listening to our customers. However, research shows that we run into roadblocks when it comes to making sense of all that information.

Customer feedback essentially falls into two categories: structured or unstructured. A good example of structured data would be spreadsheets, where information is readily searchable and falls into some pre-defined data field. On the other hand, unstructured feedback is more akin to human conversation – often characterized by incorrect spelling and lack of punctuations –  and therefore harder to analyze.

In fact, you’re probably capturing some form of unstructured feedback in Salesforce right now. For example, text-heavy files like emails, customer comments, support notes, are all considered common types of unstructured customer feedback. Despite the difficulty involved in analyzing it, unstructured customer feedback often holds rich information that points to customer sentiment, tone, emotion, and motivation. We simply cannot ignore it.

 

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Seth Grimes highlighted that 80% of the data we collect these days is unstructured. In addition, a recent study by Bluewolf revealed that 76% of Salesforce users saw data manipulation and analysis as the biggest barriers to deriving business insights from their Salesforce data.

Herein lies the problem: We’re collecting massive amounts of unstructured customer feedback in Salesforce, but we have no way of easily interpreting it. As a result, valuable customer information is omitted from analyses, and key business opportunities are missed.

4 sources of unstructured customer feedback in Salesforce you’re not analyzing:

Help desk: If you’re part of a team that uses Salesforces’ Service Cloud then you’re no stranger to tools like Zendesk or Get Satisfaction. Help-desk tools  are excellent for capturing textual customer feedback like call-center dialogues, case descriptions. Analyzing this feedback is useful for detecting and predicting customer patterns and behaviours. Consequently, you’ll adopt a proactive customer service approach; anticipating customer needs and resolving problems before they happen!

Emails: I’m not just talking about your customers who email you when they need help (although that’s a big source of it). Unstructured customer feedback often finds its way into emails between product managers, sales, development, marketing teams and executives. 

Surveys & product reviews: Survey tools like SurveyMonkey and product review forums like Product Hunt are great ways to gain honest and descriptive feedback from your customers about their satisfaction with your products, perceptions of your staff, or service quality. Analyzing this type of feedback can also help shorten survey lengths and uncover the reasons behind your product feedback ratings or scores. 

Live chat and community discussions: Live support chat has helped businesses communicate directly with users to gain valuable knowledge about their user experience. If your team is using Chatter to share files, forms, and Q&A’s then you’ve surely amassed a big collection of valuable insights. Combining this feedback with customer perceptions, opinions and ideas enables is an excellent opportunity to see if your business goals align with your customer needs.

Solutions to tackle unstructured customer feedback

One thing is clear, there’s a goldmine of insights buried deep within your Salesforce CRM platform. The questions is, how do we interpret and derive meaning from all that unstructured customer feedback? Two words: Text analytics. Text analytics applies natural language processing, machine learning, and visualization techniques to identify and extract information from unstructured text.

For many years, text analysis has been viewed as a challenging and clunky technical process that required the coordination of database administrators, development teams and analysts. Today, text analytics tools are designed with simplicity, user-adaptability and flexibility in mind. They empower teams to identify and resolve customer issues faster, discover new market opportunities and improve overall business operations.  Most importantly, text analysis solutions enable Salesforce users to transform all that unstructured customer feedback into actionable insights.

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