Content Maxima, a content intelligence platform, today published new semantic and buyer intelligence data covering landing page A/B testing, expanding the data available to marketing teams around algorithm trigger words and customer journey messaging. The release makes the data set available to teams evaluating landing page test variations.
Content Maxima's platform surfaces semantic and buyer intent data based on a main entity that a marketing team submits, such as a brand, product or landing page. The platform does not generate testing strategies or recommendations. It returns underlying data, including language pattern analysis and customer journey mapping, which marketing teams then apply on their own to inform test design.
"This data set gives marketing teams another layer of information to work with when they're building out landing page tests," said Edward Baker, co-founder of Content Maxima. "What a team does with that information is entirely up to them. Our platform surfaces the data. It doesn't tell anyone what to test or how to interpret it."
The trigger word data referenced in the release is generated through Content Maxima's Matrix module, which evaluates language patterns, keyword relationships, sentiment and entity structures within submitted content using a broad set of language models, according to the company. The module is designed to reflect how search platforms and other automated systems parse and categorize content, independent of any specific testing strategy. The module output includes a breakdown of entity structures and keyword relationships tied to whatever main entity a team has submitted.
Customer journey messaging data comes from the platform's Pathways module, which maps content and language patterns against different stages of a customer's path to conversion, the company said. The module returns data on how messaging patterns have appeared across journey stages. It does not prescribe what a landing page should say or predict how a test will perform. Teams working on landing pages tied to specific funnel stages can reference this data alongside their own journey maps.
For SaaS marketers, conversion rate optimization specialists, UX designers and digital marketers, the availability of algorithm trigger words data alongside journey-stage messaging gives teams additional raw material to reference when they're organizing their own test plans. The company said the data set is intended to sit alongside, not replace, existing research and testing methodology that teams already use. Access to the data does not require teams to change their existing test structure or tooling.
"Content Maxima built this module set so teams have the underlying data in front of them before they make their own decisions," said Baker, co-founder of Content Maxima. "We're not in the business of telling anyone what their landing page should say. We're in the business of surfacing what the data shows and letting marketing teams decide what to do with it."
Content Maxima's platform also includes modules covering audience persona data, industry-specific language patterns, content ideation and social repurposing, which teams can draw on alongside the trigger word and journey messaging data referenced in this release, according to the company. The company said it plans to continue expanding available data sets across additional use cases, with future releases expected to cover other stages of the marketing funnel.
Content Maxima is a content intelligence platform that surfaces semantic mapping and buyer intelligence data for marketing teams. Users submit a main entity, such as a brand, product or topic, and the platform returns data including language pattern analysis, audience persona information and customer journey mapping. For more information about how the platform's data can help teams improve landing page tests, visit https://contentmaxima.com.
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For more information about Content Maxima, contact the company here:
Content Maxima
Edward Baker
646-383-3438
support@contentmaxima.com
244 5th Ave
Suite No. 2001
New York, NY 10001
