Consumer Insights from Unstructured Data - Do You Need to Care ?

The latest buzzword batted around in the marketing circle is The Customer Journey. Customer journeys provide a critical understanding of customers, their behavior, and how they engage with brands. Tracking, documenting, and analyzing the customer experience through their perspective helps firms understand customer interactions throughout the customer journey and how to best serve customers.

IBM commissioned Forrester Consulting to do study on how Companies today are prepared for the Customer Journey. Forrester found out that only 5% of respondents felt they had a complete view of the their customers' journeys. This meant the overwhelming majority did not have a complete view of the customer journey.

Forrester's survey showed the key obstacles that Companies faced in managing the Customer Journey.

Form the survey, the lack of data analytics had been cited as one of the key obstacles.

My humble view is however not the lack of data analytics, but the failure to keep up with the availability of data analytics.

And this will get worse as more and more analytics become available with time.

I like to share with you today on a relatively new area of data analytics which is exploding in volume, and keeping up in this area will pay dividends as part of understanding the Customer Journey.

Unstructured Data now accounts for 85% of the World's Data.

Unstructured data is

• Emails

• Word Processing Files

• PDF files

• Spreadsheets

• Digital Images

• Video

• Audio

• Social Media Posts

Salesforce CEO Marc Benioff identified that the biggest imperative for customer-centric companies is to make sense of their unstructured data so as to be in a position to leverage it to better understand and influence the customer journey.

How to make unstructured data structured ?

There are three steps involved:

a) Aggregation - Different sources of data are pulled together into a repository

b) Analysis - Using tools such as data mining, natural language processing (NLP), and text analytics provide different methods to find patterns and sentiments, and interpret the data

c) Standardisation - categorizing the data into specific themes which can be be actioned on.

With the massive volumes of data being handled, algorithms and machine learning are required to manage and analyse unstructured data.

How unstructured data can be used in the Customer Journey

Mining what customers are writing and talking about your:

- Brand, Products, Competitors

- Viral topics which may be connected directly or indirectly with your proposition

This can help you take corrective action on negative feedback, and also improve on what your customers are already happy with.

With data, marketers and product developers can more confidently build campaigns and new products based on what customers actually want.

For example, you could analyse customer feedback in call-centre transcripts and identify trends in product and service reputation and faults very quickly. Or, you can analyse your social community on Twitter to find the topics, sentiments, locations of their tweets, and of the links they have shared, to build up a much more detailed picture of your followers.

What do You do Next

There are three factors to think about before investing into analyzing unstructured data:

a) If your business is largely B2C

b) You intend to leverage more on digital marketing with more social media engagement

c) You consider understanding emerging trends a key competitive advantage for your Business.