In today’s customer analytics world, customers are moving towards a behavioral-based model. What does this mean? In today’s episode of “Datameer Whiteboards,” I’ll demonstrate what customer acquisition looks like today and how big data analytics can help you move the needle.
In our last video, we looked at how customer behavior analytics based on big data can help you optimize all four aspects of the customer lifecycle:
Today, we’re going to drill down into the customer acquisition side of things and better understand how big data and behavior analytics can make our acquisition processes more effective.
In our new digital age with models based on big data, we’re moving away from a more transactional-based RFM model, or Recency, Frequency and Monetary value, into a more behavioral-based model. This will help you better:
The first thing I do is I take my customer behavior model and I map it into a customer segmentation model. I do this based on the lifetime value that these customers will bring for me, not based on the next transaction they’re going to bring to me. This will allow me to target the right customers that can maximize the long term value and spend they bring to me. Then once I have this segmentation, it gives me all the right attributes and outcomes that allow me to drive the four key areas of customer acquisition.
The first thing I want to do is better optimize my channel strategy. I want to better understand where can I find the best prospects that meet the profile that I want. By better understanding this, I can target the right channels which will increase my conversion rates and also reduce the amount of money I need to spend to acquire those customers.
Secondly, I’m going to map behavior to outcomes to best find the right offers that these prospects will respond to. This allows me to give them the right in-the-moment offer which will help increase conversions rates.
Then third, I’m going to map behavior across all the various touch points and interaction points I have with customers so I can map the overall customer journey that they take. Therefore I can see where I am being most effective in walking them down this journey, and where I may have lost them along the way so I can best optimize my path to purchase.
Then lastly, I’m going to take some of this behavior data and create predictive models. Using these predictive models I can identify the prospects that are most likely to purchase from me and I can spend more time focusing my effort on acquiring these customers that are most valuable to me.
In conclusion, we can see that customer behavior permeates throughout the entire customer acquisition process, right? It allows you to find where you can find the right customers and how you can present the right offer to particular customers to better convert them. In addition it enables you to ask, what is the right journey or path you need to lead customers down to best convert them? And lastly, which customers will bring you the most value?