Data analytics can be confusing for many executives. Big Data is a complex subject and the analysis of large sets of constantly changing data is often left to the data scientists rather than being considered by the executive team. This is a mistake and there are many reasons why you should be exploring customer analytics in more detail.
First, it is worth considering exactly why this is now so. Look at what my colleague Johnny Mortensen wrote in a recent article:
“This evolution in the role of the contact centre underpins the power of the modern contact centre to increase revenue. The modern contact centre is no longer just handling post-sale customer complaints or questions; the contact centre is defining the customer experience and therefore defining how customers see the brand across all channels.”
As Johnny describes, your customer service function is now the key interface between you and your customers. It is no longer just a channel for post-purchase complaints, it defines the relationship between you and your customer and therefore if you can understand your customer better then you will have concrete opportunities to increase revenue.
This article explores some of the reasons why online shoppers do not complete a sale. Some issues include:
- Unexpected shipping cost: 25%
- Having to create a new user account: 22%
- Was researching a product I intend to buy later: 17%
- Payment security concerns: 15%
- Long and confusing checkout: 9%
Now the need for a better understanding of data analytics becomes more obvious. Some analysts believe that online retailers are losing 75% of their revenue because shoppers start out selecting items, but never complete the sale.
Just imagine if you can understand why such a large proportion of potential customers are being discouraged or prevented from completing the order they started. Look at the question of shipping cost for example. If you can reduce or remove the shipping charge, or even just make it easier to understand, then you could potentially convert 25% of all those abandoned sales into revenue.
Data and analytics may seem complex, but really we are just trying to understand the customer better. Once you have these insights then actions can be taken that will lead to real revenue increases – that has to be interesting to every executive.
Let me know what you think about using customer analytics to increase revenue by leaving a comment here or get in touch via my LinkedIn.