A SiriusDecisions report identifies 70% of the B2B content that organizations produce go unused. According to an Aberdeen report, only 44% B2B marketers have a documented strategy to promote their brand. Most content marketers identify challenges in their content marketing strategy, including the lack of time, evaluate the quality of content that engages audiences and determines the ideal volume of content. To help CMOs overcome content marketing challenges, BlueConic announced the introduction of BlueConic Recommendations Engine on its customer data platform (CDP). The new engine enables marketers to automatize their content delivery processes, delivering 1:1 content and product recommendations in real-time.
“Companies are seeking more effective ways to connect with and engage with consumers, as online competition grows daily, says Bart Heilbron, Founder and CEO of BlueConic.
“Recommendations for a single person challenges the industry standard in order to help marketers increase customer loyalty and sales. BlueConic has developed an incredibly easy way to integrate high-value recommendations into existing marketing processes and campaigns.”
BlueConic Recommendations Engine allows B2B marketers to benefit from readily available content to increase customer engagement over cross-channel platforms, helping audiences to drive purchasing decisions using high-end personalized information.
How is BlueConic Recommendations Engine different?
Traditional content recommendations tools identify traffic-based content or products that received the highest clicks from all omnichannel platforms based on demographic segmentation. The BlueConic Recommendations Engine uses ingeniously built machine learning capabilities that combine individual user profile data with key data attributes and metrics to deliver recommendations, aligning with individual user behaviors and preferences. By adopting recommendations tools, B2B customers see a significant rise of 30% and 50% higher click-through-rates compared to existing recommendations tools.
BlueConic uses Apache Spark big data processing technology to handle the high-volume machine learning tasks required for real-time recommendations.
Technical capabilities of the BlueConic Recommendation Engine include –
- Automatic incentivization of all profiles, content and statistics data in minimum clicks
- Scalable recommendation engine for SMBs and mid-sized B2B companies that handle variable amount of data with a pluggable, extensible set of algorithms
- Recommendation delivery engine that can be placed in any format, to be used across channels and devices
- Out-of-the-box and easily configurable dashboards for marketers to view results by the number of views, clicks, and conversions for every recommendation in real-time and historically
Why you need recommendations engine in your MarTech stack?
Most CMOs agree that they would rather invest in a content strategy that offers organic ROI-compounding opportunities. According to Hubspot report, compounding blog posts generate 38% of all traffic, allowing marketers to turn content into a key inbound marketing stack. However, 55% B2B marketers are still doubtful about what content marketing engagements depends on, in case there’s no legacy document.
By adding the latest Recommendations Engine, BlueConic users can drive more engagement for a compelling value proposition with real-time audience profiling that maximizes ROI of advertising campaigns.