Lift Taking Off...
by Katelyn Fogarty
It's been awhile since I've written an update about my integration of Lift into the Acquia.com site (you can read my last post here), but recently I've been getting some results that are worth sharing.
The numbers aren't big, because I've only been running this latest test for about a month, but they are impressive enough that the sales team here took notice.
In fact, Tom Murdock, head of worldwide inside sales here at Acquia, got very excited when he saw the latest Lift results.
The small numbers didn't stop him from sending an email to the entire sales group, "sharing some great metrics regarding Lift's impact on our acquia.com conversions."
What Tom reported to the team was impressive.
Post-Lift deployment, he wrote, the results were:
- 2x increase in traffic clicking on our Calls to Action
- 3x increase on those who took action becoming a Lead (filling a form to talk to sales, download an asset, etc)
- 6x increase on the conversion from Traffic to Lead
The key, he wrote, is, "a combination of great content and making sure that content is being surfaced to the right person."
My inner metrics geek insists that I remind everybody, including Tom, that these numbers are too small to be statistically significant. But you have to love the way the trendlines are moving.
Acquia Lift, btw, is a personalization solution that allows digital businesses to deliver the right experience, to the right person, at the right time, in the right channel, in real time.
The big idea behind Lift is the next wave in engagement - contextualization - which includes personalization, plus behavioral targeting, rich audience segmentation, content recommendations and offers, and the use of existing enterprise data sources to deliver smarter and more relevant content.
Lift actually consists of three modules: Target, which allows users to focus on user segments, test experiences -- and automatically implement the best results; Recommend uses advanced algorithms to enable the promotion of the best content recommendations and offers; and then there's ContextDB, which unifies visitor intelligence and customer behavior from multiple channels and existing systems into a richer, progressive profile to drive contextual experiences in real-time.
What I've been using, lately, is Lift Target, to collect comprehensive visitor profile data (audience segment and behavior), historical data (past behaviors and interests), and situational data (what’s happening with the visitor right now, for example, time of day, geolocation, device, browser).
I've been using it alongside Demandbase, to help target content to the industry or company of the visitor.
What I've been doing is using the Lift/Demandbase combo to test different assets with calls to action (CTA) on the page, to see if an industry-specific asset resonates with that specific industry, compared to the default assets that we normally use in that section.
Here's the section of the front page I've been working with:
And here's the section with two industry-specific assets, targeted at the education vertical. Those two assets are examples of what we've been using Lift and Demandbase to measure.
So far, we only have less than a month's worth of data, collected during the Thanksgiving/Christmas holiday season in the US.
But our sales guy, Tom Murdock, is right to be excited.
Although the numbers are small, the percentages are very promising: a 2x increase in traffic clicking on our Calls to Action, a 3x increase on those who took action becoming a Lead (filling a form to talk to sales, download an asset, etc), and a 6x increase on the conversion from Traffic to Lead.
Again, the data we've collected so far is tiny (have I mentioned that?), yet Tom -- and I -- see it as an early indicator worth paying attention to.
I also think these results are worth sharing with a broader audience (that's you) as a kind of preview, and a promise: as they get bigger, and more statistically significant, I'll keep crunching them so that all of us can get closer to delivering the kind of personalized, contextualized experiences we want our customers to have.