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Analytics Now Available In Acquia Lift

"Data! Data! Data! I cannot make bricks without clay!" -Sherlock Holmes

Delivering personalized experiences requires data. The more data, the better the experience. And when that information also takes context into account—information about the preferences, behavior and interests of your visitors—the more powerful the possibilities become to provide a relevant, engaging experience.

Acquia Lift builds a profile from all available data for every person that interacts with your brand. This includes the content that an individual is most interested in, their level of engagement, their historical behavior, their geography, how they were referred to you, and so on. It can also integrate with other channels and systems, such as Marketo, to pull in their stored data and stitch together a comprehensive picture of the customer across their the various devices and identities into a single, unified profile. This ongoing stream of visitor data is matched in real-time to segments in order to enable Lift’s testing and targeting capabilities.

But what’s data without measurement? We’re excited to announce that with Lift’s recently launched analytics capabilities, it’s easier for customers to not only capture data but also understand it. Lift customers can now start to measure the impact of their personalization efforts, identify optimization opportunities, and gain insight into their users.

Introducing Acquia Lift Analytics

Lift now features a powerful analytics engine, complete with a series of pre-built reports and dashboards that help customers answer questions such as:

  • What does the customer journey look like?
  • How do my different visitor personas behave?
  • How do my different segments of visitors perform?
  • What content resonates the most with different audiences?
  • How is visitor engagement trending?
  • How are my campaigns performing?

The new analytics in Lift was built to provide insights that help customers better understand their audiences and achieve their personalization objectives. It is not intended to duplicate the extensive information that you already obtain from your existing web analytics tools but rather to supplement it. For example, providing a report for "bounce rate" in Lift is probably not that interesting, since that is web-centric information readily available from Google Analytics. On the other hand, showing the number of unique people by Lift persona or segment that reached a certain goal can be very useful information for a marketer who is assessing the effectiveness of their personalization campaigns.

Lift Dev Persona

Six month trend of number of people in the Lift “Developer” segment who filled in an inquiry form

Lift’s analytics was designed to ensure that reports and dashboards run quickly. The immense amount of data in Lift can take time for an analytics engine to crunch, but customers don’t have time to waste waiting for results. To ensure that performance is fast and efficient, we combined the power of Amazon Redshift, a petabyte scale data warehouse, with pre-built aggregations for every report and dashboard that are refreshed nightly. This means that most reports and dashboards will run in seconds, despite millions or trillions of rows of visitor data being involved.

Lift persona
Conversion rate and average time, by persona, of people who filled in an inquiry form

Available Reports

Documentation on the over 30 new Lift reports and dashboards can be found here. They are broken out into the following topic areas:

  • Content - Insights into which content performs best, optionally filtered out by Lift segment or goal event.
  • Conversion - Insights into which people reached a particular goal event, optionally by persona or content keyword.
  • Engagement - Insights into engagement scores, the number of page views over certain periods of time, and the amount of time a customer spends on your websites, optionally filtered out by goal event.
  • Events - Insights into event trends, optionally filtered by Lift segment or goal event.
  • People - Insights into people, broken out into facets such as geography, persona, segment, favorite content, etc.
  • Segments - Insights into segment performance, such as which segments reached a particular goal event, or which segments tend to be in common with other segments.
  • Touches - Insights into where visitors are coming from and what kind of platforms they are using.

We hope you like the new analytics capabilities in Lift. Stay tuned for more to come!

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