Built for marketers, Lytics customer data platform (CDP) collects and analyzes first-party behavioral and affinity data based on the actions your customers take in your mobile app, online ads, website and marketing emails.
Then its machine-learning decision engine gives your marketing team the insights they need to deliver personalized marketing experiences in real time through your digital channels.
Many B2B companies face technical, organizational, and budgetary challenges that hold them back. With Lytics CDP, B2B marketers can use machine learning insights to personalize their marketing and deliver results.
With data stored in multiple platforms and first-party data inaccessible without IT support, B2B companies need to break down technical silos that prevent them from using the data they already have.
Customer profiles must pull data from various marketing and IT data sources and also be linked to company accounts at different stages of the buying process before marketers can deliver relevant content.
Inability to create accurate segments in ad networks and poor visibility into which marketing campaigns are delivery results prevents brands from targeting the right audience with advertising.
Companies using content marketing often struggle to understand which content is most effective, especially when their prospects work in different industries, have different job titles, and play different roles in the buying process.
Your company’s customers may be other large organizations, but the people who make the decision to buy are just that: people. They have their own roles, responsibilities, challenges, and preferences.
And you have to be aware of them to market to them successfully. That might mean delivering content that’s suited to their role or that reflects where they are in the buying process.
Lytics content affinity engine analyzes your digital content and measures visitors’ interactions with it, so it can deliver the content that matters most to them in real time.
Use visitor behavior data to drive on-site, real-time content recommendations across digital properties (websites, apps, and blogs) and channels (email, ads, and SMS).
Use machine learning, behavior scoring, and predictive analytics to deliver relevant experiences to team members based on their roles and responsibilities.
Predict how likely given users are to progress to desirable (or undesirable) lifecycle stages, then take actions to increase the likelihood of favorable outcomes.
Rather than accumulating data of dubious value in a data lake or warehouse, focus on key behavioral data that predicts outcomes and provides insights you can act on in real-time.
Companies looking to extract value from their data turn to Tableau for visualization software. But to get the most out of their data, Tableau built a best-of-breed CDP stack featuring Lytics as the decision engine.
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