We’ve now seen how data is evolving to transform organizations in the retail world, but what about a B2B company? Let’s discuss how a B2B company can benefit from streamlining all their data analytics systems into one system.
While the structure of the information flow here is very similar to retail companies, albeit with different goals, the data generated is applied differently on a tactical level.
Let’s begin with the data structure:
First, collect data from multiple sources
We have two initial points of data collection. We collect data when a user visits the site and when they fill in the lead form.
We can use the data factors from when they visited the site or landing page to help qualify the lead as we learn more about how other qualified leads have visited the site or landing page.
How long did they spend on the site? How many pages did they visit? What elements did they click on? All of this is instrumental in finding common behaviors amongst leads.
Then, streamline information into a data analytics system
After a lead comes in, we can use 3rd party data to find behaviors that are most likely to occur within a lead. For example, if we use Experian clusters along with data analytics systems, this is data that can be passed through to the pre-sales and sales team. They’ll know a lot more about customers and it will help make personas statistically a lot more relevant.
Depending on the data analytics systems you use, there is also a chance you can see a bit about the sites your potential customer visited prior to your site. This could give great insights into the other products your customers are considering.
Next, use data analytics systems internally
On the product side, we should be able to track exactly how our customers use the product and where they came from. We can use a combination of lead form data and usage data to build out product extension lines. Perhaps customers like these purchased or upgraded to other products your company may sell as well.
Any data we find internally should also go back into the DMP so that the marketing team can try and target external users. Depending on what is important to you, these insights can be pulled into your marketing campaigns to try and draw in leads that behave more like your most active users or maybe your largest contracts, again depending on priority.
Finally, the marketing team optimizes on this information
Thanks to a lot of the technology available on the market, almost any data can be used to build increasingly efficient marketing campaigns.
Find your most valuable users and combine that 1st party data along with 3rd party data and you will find that in the right algorithm, your cost per lead will drop dramatically while the lead quality becomes significantly better.
Central Data Analytics Systems Improve the Bottom Line
The end goal and result of a central data analytics system is ultimately to make our companies not only more informed about the people who buy our products but to make us increasingly more efficient.
Data is going to help us reduce support ticket times, decrease user confusion, decrease lead cost, increase contract size, and make our companies more valuable.
Isn’t that where we’re all trying to get to anyways?