As markets become increasingly globalised, saturated and competitive in the digital age, great focus is being placed on the customer experience.
And, in periods of subdued or stagnant economic growth, such as South Africa is experiencing, people slow down on their spending and as a result, it becomes harder to attract new customers.
Therefore, in these challenging times, significant emphasis is focused on reselling, cross-selling and up-selling existing customers.
However, there is only so much about a customer that can be discerned from their monthly account balance and credit bureau data, where in many cases, whatever insights were available in this data have already been obtained. Businesses therefore need to look beyond the two-dimensional data available and seek other sources of information or insights that will assist the company to better understand customers. To answer the ever-elusive question: Why?
For many years, data warehouse and business intelligence (BI) solutions were focused on defining the what, when, where and how of a company's business.
Sadly, I think that in South Africa we are still a bit behind in truly understanding how much this social data can assist us.
Very often, the 'why' was not possible. In other words, understanding why good or bad things happened in a company. This was where advanced analytics (AA)/data science came in. Trying to understand why things happened was deemed to be the responsibility of the relevant AA department.
The reality though, is that even with AA, understanding the why was still not really that easy to do. AA could maybe tell you why a division was doing badly, or what was causing customers to churn. However, we were never able to truly understand the why.
We could make reasonable guesses and extrapolations, but this was generally only at the surface, skin-deep level. The reason for this was that we did not have the detailed information available to get into the hearts and minds of the customer. We could make predictions based on the two-dimensional data available to us at the time, but no more than that.
With social data becoming more available to BI teams, we are now able to dig deeper, into the psychology of the customer. We are exposed to more information that can help us determine what is going on in our customers' lives. With this, we can better understand the motivating factors behind customer behaviour and the why.
To do this, we obviously need more data, and there are a few factors that we should consider here.
Data access
Some social data is readily accessible, but many platforms have more security restrictions, where you need a valid connection (and permission) to a person to access their data. It's not the Wild West!
Making sense of the data
Having all the social data in the world won't help you if you cannot make sense of the data. In this regard, the human touch is extremely important, in terms of correctly managing and categorising this data.
Natural language processing is a must! This is a large topic, so keep an eye out for a subsequent Industry Insight focusing more on this.
Alternative, costly data sources
There are also other sources of data, such as news sources, that can provide significant additional context. Some are free; however, many of the good ones are not.
As such, the price needs to be factored in. It might not technically fall under the banner of social data, but it will require similar skills to process and make sense of the underlying sentiment and context in the data.
The human factor
Sometimes, the biggest challenge is a human one. Just having people in an organisation, in both business and IT, who can see the opportunities and raise the necessary funds for implementation, can be the biggest obstacle.
Sadly, I think that in South Africa we are still a bit behind in truly understanding how much this social data can assist us.
Got the data, now what?
Once the data has been obtained, there are many potential use cases. For instance, the data can be used to create a map of what is going on in the customer's life and provide businesses with a view of how this intersects with, and impacts on, the brand and its products and/or services.
More relevant, targeted interactions with the customer can occur, due to a greater (and hopefully more intuitive and empathetic) insight into the customer's life.
Convergence
It is important to remember that recently, there are many new trends, technologies and capabilities that have one or more points of convergence with other related concepts.
With social BI, this is no different. I believe this concept converges strongly with the Internet of things, big data and analytics. The convergence opportunities can provide significant improvement to customer selection, sales and service.
Imagine having a 360-degree single-view of the customer that is updating in real-time, based on the customer's movements, buying behaviour, biometrics and social sentiment (targeted at specific products, brands or concepts).
The implementation of such solutions elevates the role of data and BI in the organisation beyond that of traditional reporting and analysis, traditionally last in the value chain, and places it front and centre of the organisation's perspective. An important enabler of many new, modern initiatives.
Lastly, I need to caution and remind you that while the possibilities are endlessly exciting, it can be interpreted as creepy and invasive to customers. So, remember to be fully transparent, and ensure you have compliance and ethics in the forefront of your mind when starting this new and exciting journey.
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