One of the biggest challenges of any business is to grow their business through effective marketing. As a Marketing manager, you want to understand your customers, what they want and what really drives them, so that you can sell to them more effectively. And you want to do this quickly and without having to depend on IT or pre-requisite expertise.
Watson Analytics can help you do that and much more without any expensive or time consuming setup or training.
Analyze using natural language:
Let’s see how that works with an example!
I want to assess the performance of my email campaign in the Western Pacific states in US. I also want to take a look at my customers’ lifetime values and more importantly understand what drives those values.
I begin my discovery by typing my question in natural language right here on the Watson Analytics welcome page. The built-in cognitive ‘smarts’ looks across datasets to fetch my answer and then ranks them in order of their relevance.
Find who are responding:
I immediately realize that the campaign was not a huge success and that’s not very encouraging!
At this point, I could also change the focus of my analysis by using the interactive titles – like I can change Response to Education or say Coverage, etc.
However, I want to delve deeper to get a sense of the Yes responders shown in green.
I keep the ‘Yes’ respondents and keep digging to see what is driving them. By changing the view I can quickly see that the second offer is actually more important to focus on. Something that in a spreadsheet would be hard to discern and because of the powerful charting capabilities in WA, that becomes very obvious very quickly.
Know where they are responding from:
Let me focus on Offer 2 and Drill Across to see what States those customers were from. Watson Analytics automatically rendered a tree map that shows me the distribution of my Customers who responded as ‘Yes’ to Offer-2 across States. California and Oregon stand out among the other states.
This is helpful but I wonder if there is more to the story. Adding data to the chart is easy, I’ll add Policy Type – Policy roll up that the smarts of Watson Analytics dynamically created for me. I’ll then want to drill down into my biggest Policy Type which is Personal Auto while keeping all my existing filters.
I open a new tab in my discovery set to explore further. This time I use on one of the suggested starting points that Watson Analytics has generated for me and click on the Income by State map visualization. I modify the map to now look at the average Customer Lifetime Values and the number of Customers across these states. While Oregon has a slightly higher average Customer Lifetime value, California has the higher concentration of customers.
Also note the cognitive insights bar on the right that dynamically surfaces insights relevant to the visualization that’s being discussed. I click on first recommendation (as highlighted in the image below) – ‘Top Drivers of Customer Lifetime Value’.
Understand what really drives customer lifetime value (CLTV):
I’m getting a picture of my campaign results, but of course, what I really want to know is what I should do looking forward.
Who are my most profitable customers and what drives them?
Understanding these aspects will not only help me retain them but also to up-sell and cross-sell to them.
That’s where Watson Analytics’ built in predictive analytics come in.
This easy to understand spiral visualization shows me the factors that drive my target, in this case, Customer Lifetime Value, in order of their importance. Looks like the combination of vehicle class and number of policies has the most significant impact on my target and drives it with 65% predictive strength.
Identify the right target market and course-correct (if required):
The devil is in the details and I surely want to dig deeper!
Clicking on the associated detailed insight for the top combination, I can see the sweet spot for Customer Lifetime Value is at the intersection of the Luxury Vehicle Class, which comprises Luxury SUVs and Cars, and the Number of Policies. So essentially that’s my target market and that’s great insight!
Bring it all together:
Finally, after I explored my data, I can bring it all together in Display.
I create a new Display by choosing an appropriate template and start building my dashboard by dragging and dropping visualizations from my saved discovery sets – in this case I use the discovery set that I just created. I can choose from a variety of layout and formatting options to create interactive multi-tabbed dashboards. I can assemble, format and even edit my saved discoveries and visualizations to generate a better understanding of how my campaign is performing.
Here I added two local filters viz. Location Code and Gender and filter my dashboard on only on females from non-urban locations. Looks like Nevada could be a huge potential for us to grow this market!
To summarize, I started with just a question and within minutes I was able to understand more about our email campaign, how they were received, our policies & offers and more importantly, what really drove our Customer Lifetime Values. With these insights, I’m better placed to focus on our strengths and maximize our marketing and campaign ROI!
Use Watson Analytics to discover, display and share your findings with ease and agility!