Actuate recently announced a new version of Birt Analytics, the in-memory visual analytics offering based on technology acquired from Spanish software provider Quiterian in 2012. The latest release (v 4.2) now includes several enhancements in the areas such as increased algorithm support, automated data loading and analytic campaign workflows.
Part of Actuate’s strategy for acquiring Quiterian (as we wrote about here) focused on targeting the offering towards business users and capitalising on its self-service exploration and analysis capabilities, thereby bypassing the typical audience of these tools such as IT developers, highly trained statisticians or data scientists. Sales and marketing professionals seem obvious candidates for the offering since they are (usually) responsible for the analysis and measurement of marketing campaigns or sales initiatives and hence suit the tools highly visual interactive analytic capabilities.
By extending the number of algorithms it supports—in particular around association rules and decision trees—Birt Analytics is now able to tackle a wider range of sales and marketing scenarios. For example, association rules can be used to underpin market basket analysis for identifying items that frequently match other items in transactional data, typically used in up-selling or cross-selling activities, whereas decision trees can be used in offer targeting to help organisations pinpoint customers for a loan offer, for example. While these aren’t the only analytic use cases in practice, increased demand from marketing and sales organisations means they are some of the most popular. Actuate obviously recognises this need—as do many other analytic vendors.
Extending support for its algorithms however isn’t by itself enough to guarantee success for Birt Analytics. Our research suggests that marketing and sales business users increasingly want a more intuitive, guided and automated analysis experience that helps them get to more accurate insights, faster and easier. Birt Analytics goes some way to support these requirements. Underlying the offering is an in-memory columnar database proficient at processing millions of rows of structured data. This, combined with some rich visual capabilities, enables users to quickly and easily explore the data to identify customer segments, identify the strength of a correlation between attributes in that segment, help classify clusters and examine the most important factors influencing customer choice.
While Birt Analytics makes the customer analysis piece look relatively straightforward to a business analyst, what perhaps is missing is a more seamless way of integrating these insights or customer lists into a marketing automation tool. Although version 4.2 has introduced a campaign workflow into the tool, this is focused on automating the analysis component of a campaign rather than its operational execution. Being able to articulate and flesh out its partnership and integration strategy with marketing automation vendors should remain a priority for the company.
All in all the new version of Birt Analytics offers some welcome analytic enhancements that play very nicely with the demands of marketing and sales users. Continuing to extend its analytic reach in complementary areas such as propensity modeling and sentiment analysis should remain a longer term goal for the company.