How algorithms help brand promotion?

Retail customer image by Motorola Solutions

Digitization is changing the way customers shop and companies promote their brands. Data-driven insights are revolutionizing both customer experience and brand promotion by giving relevant choices to buyers.

Reaching customers in every possible way is key to businesses and in the digital era, where one tap on smartphone does things for us, brands will be compelled to look for innovative ways to generate leads.

From e-mails to webpages to apps, we now see various brand promotions in accordance with our most used keywords while searching our brands and preferences.

That algorithm, nicknamed as brand-gorithm in this specific context, now plays key roles in influential marketing.

Nate Woodman of IPONWEB defines brand-gorithm as a proprietary algorithm unique to a brand and used to make decisions such as how much to bid on an impression or what message to serve.

A Gartner write-up by Martin Kihn notes that most brands already do some of this. Whenever a personalization platform comes up with a next-best-offer model or a marketing automation system scores leads, they’re using some proprietary data and machine learning methods to do it.

What the brand-gorithm brings is a more comprehensive, omnichannel and machine-driven master model.

You can see promotions in a webpage you are browsing, or in between a video streaming, or during game breaks. Ultimately, these types of automated marketing benefit businesses as they get personalised attention.

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According to Gartner, Amazon and Netflix are lighthouse examples of companies with vast inside data and predictive powers. They’re a window into what should be possible for other brands in future, a world where, as Netflix’s chief product officer once said, “There are no bad shows, just shows with small audiences.” Meaning: Even your duds can find a buyer, if you know how to spot him.


The biggest obstacle to data-driven brand-gorithm is data itself. Finding the right data from the huge heap is critical for customers’ clear navigation and recommendation.

For that, an organization requires an accurate cross-device, cross-channel identity in addition to a clean set of features, the things you know about the prospect or customer.  In reality, all this is harder than it sounds.

Furthermore, a lot of data from a lot of observations is required to train a useful model. Even if all these hurdles are crossed, the marketer faces the real problem of execution.

Owned platforms, such as websites and email, should be able to act on the decisions. But anything outside the marketers’ walls will need APIs or other connections that are flexible, nuanced and fast.

The harder barrier is that more of the web is closed to brands. The information is captured, but it is held for the benefit of large walled systems. And because they see more of their own users’ lives than any brand, they’re in a position to build more accurate predictions.

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Forrester’s recent research said the brand-agency relationship model is broken. Only 50 percent of marketers are satisfied with their lead agency, and more than 60 percent are open to outsourcing agency work to consultants. Forrester recommends that marketers must implement a four-step approach to build a brand-agency operating model.

According to Forrester, apart from tech like VR/AR, AI and IoT, some of the other top emerging tech that marketers should have on their radar include content intelligence, customer journey analytics, enterprise preference management, intelligent agents and automation.

Arya MM
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