Reach Analytics offers its cloud-based analytics service to businesses that wish to clean and optimize their contact lists. This helps free marketers from the confusion of duplicated data gathered from multiple sources such as mobile apps, online contact forms, and social media.
Inte Q, a marketing and analytics agency, is no more immune to the ill effects of duplication and confusion than any of its counterparts, so it has chosen Reach to smooth its data stores, which in turn should improve the outcomes of Inte Q enterprise clients.
Reach indicates on its website that its primary goal is to help marketers like Inte Q identify their best marketing prospects by analyzing customer data in the cloud and then producing reports of details such as customers’ geographic locations and socio-economic factors. Reach also uses machine learning to produce lists of the “best” marketing prospects – a feature that lies at the heart of Inte Q President Steve Kietz’s praises of this relationship.
“What’s impressive is how Reach has automated the entire process – from model building to customer profiling to prospect generation,” Kietz said. “Honestly, what they do is amazing and incredibly innovative. Their ability to analyze customer data and profile consumers is way beyond what anyone is doing in the market. Other companies say they’re doing the things that Reach is actually doing.”
The actual processes that will take place at Inte Q offices should look something like this:
Marketers must first choose which path they would like to take on their next assignment. They can see which customers best reach to a product line, live in a specific geographic area, are more likely to respond to channels such as mobile or web, or who prefer visits to brick-and-mortar locations. Then, after having made that decision, they can process a collection of customer data in Reach’s cloud to show which individuals will best fit the model of attack.
Ultimately, this takes the burden away from marketers in trying to predict which customers will make a good fit for a marketing campaign. Bruno Delahaye, the CEO of Reach, noted that the use of his company’s product removes the complexity of that situation while also offering an effective end result. In the past, marketers had to make a lot of assumptions about how customers would react to specific stimuli and marketing channels, and they often found themselves in the wrong. Reach tries to turn that pattern on its head.
Reach indicated that it uses information about populations that is less anecdotal and fragmented than marketers may have used in home-grown operations. Delahaye and company must be more robust in its assertions, backing its claims with meaningful customer data. Kietz’s comment shows that, at least, this partnership is off to a roaring start and has the potential to continue this way for some time.
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