Revolution Analytics is a predictive analytics company that specializes in the open source programming language known as “R.”

Big data analysis is a highly competitive marketplace with a number of powerful, competing firms like IBM, SAS, and Tableau.

Consequently, segmentation is key to getting Revolution Analytics in front of the right audience.

Engagement Goal

Portent was contracted to improve Revolution Analytics’ conversion quality while trimming CPA.

Revolution Analytics Results

Results at a Glance

  • Improved PPC click-through-rates by 240% leading to a 33% total lead increase and a 47% drop in cost per acquisition
  • Enhanced lead quality due to a paid search budget focus on the highest profit lead-types


In order to achieve Revolution’s goals, Portent developed an overall strategy to reach higher-value customers.

Tactics employed included:

  • Making significant ad copy adjustments, including implementing clear calls-to-action, using dynamic keyword insertion, adding keywords to copy, and creating two distinct phrases within each ad (separated by a period) which allowed for ads to be shown in top 3 spots more easily
  • Quality score improvements aided by better CTR, keyword relevance, and strong account history – as a result, we saw better average positions for core non-branded phrases, leading to more conversions at a lower average cost
  • Keyword Match-types changes
  • In the previous year, a large portion of the keywords in the account were set to broad match
  • This left us with a large portion of the keywords in the account set to modified broad, phrase, and exact match which led to increases in CTR and conversion rates


Once we began this approach, Revolution’s lead quality improved dramatically. Even as the business shifts focus to new markets in the big data space, Portent’s approach adjusts, advising the client on new content and landing pages targeting the expanding audience of big data analysts.

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