Cognitive ROI launches DataPOEM Plug & Play version
Launched originally in 2019, DataPOEM is an AI based SaaS platform that works on the principles of “deep learning” technique, powered by the wisdom of marketing & AI domain experts
Cognitive ROI Inc. has launched the DataPOEM Plug & Play version.
Cognitive ROI is a ROI measurement tech start-up company registered in the state of Delaware, USA. Launched originally in late 2019, DataPOEM (POEM inspired by Plan, Optimise, Execute and Measure) is an AI based SaaS platform that works on the principles of “deep learning” technique, powered by the wisdom of marketing & AI domain experts.
“Existing ROI measurement methods offer a post facto partial view of the marketing ROI challenge, which seldom have tangible real-time implementation value at the grass root level. Exploiting today's technology and data analytics using Artificial Intelligence based algorithms, DataPOEM will enable marketers to metamorphose from the conventional methods and silo media-centric cost efficiencies alone,” the company said.
DataPOEM addresses the few core challenges of marketers, comprehensively:
- optimum combination of marketing channels & how much to invest in each of them?
- to scientifically choose from 500+ marketing channels across all media and on-ground opportunities
- to know which of these influence their consumers, resulting in sales or other business KPIs
- more importantly, to understand these in near real time and not post-facto
For marketers who are driven by imagination but seldom have access to real-time insights, DataPOEM is a prized weapon to impact today’s inter-connected consumers. And save precious marketing dollars too. DataPOEM is able to pinpoint the causal impact of a brand's marketing inputs on the consumers’ purchase process, which is non-linear today.
With the new launch of revolutionary Poem365 from DataPOEM, no marketer will be in the dark about what works and what doesn't. It goes beyond cost efficiency metrics of a particular channel and enables marketers to comprehensively measure the impact of each of their marketing stimuli, viz. offline and online media, below the line trade & consumer promotions, creative renditions, sponsorships et al.
This ability to provide causal attributions, even in a cookie-less world, is unique and is unlike other methods which conjecture results or merely measure silo effects of a particular medium or platform.
Plug & Play version for ease of use : In its endeavour to help marketers best plan for their future demand generation, DataPOEM enables one to answer what-if questions for scenario analysis, taking into consideration the market dynamics and all variable factors that impacts the final consumer outcomes. Differentiating itself from other clunky analytics solutions, DataPOEM helps marketing analytics teams with its plug and play. With over 191+ API integrations and complete automation of data ingestion and standardization, DataPOEM eliminates the data drudgery that precedes any meaningful recommendations and insights.
As a net result, DataPOEM promises to save at least 20% on the marketing spends, even before one gets down to the negotiation table.
Bharath Gaddam, Founder of DataPOEM, explains: “Our proprietary always-on learning engine understands the causal impact of the different marketing activities in a dynamic way granular way. As the engine is an automated continuous learning engine, marketers can also make decisions in an agile manner (monthly or Quarterly). The Platform is built in such a way that any business manager with the What if questions can get answers without the worry of data unification, AI modelling and forecasting tools”.
Sathyamurthy Namakkal, Co-founder of DataPOEM, adds “Many clients invest substantial outlays basis cost efficiencies of what they believe is working. In today’s dynamic consumer world, they are keen to know what is really working for them at the marketplace without too much drudgery or jargon. When we set out on this journey, we were clear that we will offer a cutting-edge solution that not only shows the mirror but is also able to explain these findings, simplistically.”
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