The previous post examined a B2B example of integrating web analytics into predictive analytics and the data warehouse for online to offline conversion optimization. Now, let’s look at one more example. This time from B2C at the hand of a nifty client of Unica’s in the real estate industry
For competitive reasons, the company asked that their names not be published. As you can tell from that, these analytics are of a caliber that helps this company compete on analytics.
What is a Marketer to do these days!
Marketers get flak from consumers when they spam or interrupt them at unwelcome moments.
And so a marketer may lean back from push marketing and switch to pull marketing, i.e. let consumers drive and self-service their needs.
But then it won’t take long before the marketer will get flak from the CEO for not being pro-active and driving as much business as they could.
Dammed if you do, dammed if you don’t, it may seem.
Intelligent middle ground
This real estate industry company is choosing a clever middle ground by feeding web analytics data into predictive modeling.
They are using web analytics (in this case Unica’s NetInsight in two ways:
First, the traditional way, i.e. reports and analytics to make web site and advertising better.
But secondly, web analytics at the level of individual visitors to their web site. Key behavioral data is accessed in the web analytics data mart including visitor:
- length on site
- number of pages viewed
- key site events that may signal significant engagement
This behavioral data is fed into Unica’s predictive analytics module.
Besides web analytics data, the predictive analysis is also fed with data from the customer registration database, e.g. stated real estate buying / selling intentions and parameters.
The sausage making
A linear regression model predicts the likelihood for each visitor to be serious about a real estate transaction in upcoming weeks. Rank ordering registered site visitors by this probablity allows the company to reach out to the top candidates at each moment in time.
More precisely, the analytics are used to prioritize who will be contacted by email campaigns vs. who is ripe for an outbound sales call. The sales force automation system used by the company literally bubbles hot and ripe leads up to the top so they get addressed first.
The targeted approach makes both the customer service team and the outbound campaign management efforts that much more successful.
To be precise, the company achieved 22% lift out of their predictive models.
Multichannel metrics pay off in real Dollars (Euros, Yens, …).
The implementation phase
Let me finish with a big thank you to marketing services provider, Amberleaf, who were the services company that integrated multiple Unica products ranging from web analytics to predictive modeling, campaign management, and lead management.
Our real estate industry client has had access to a web analytics web data mart for many years already. But connecting the dots between web and customer analytics into marketing and sales management applications still required an extra step.
It took the combination of a visionary CEO and an experienced, yet affordable, systems integrator to pull it off.