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How Analytics Can Lend Relevance to Marketing


How Analytics Can Lend Relevance to Marketing


Put out of context, even the best of ideas, strategies, content, or people, become irrelevant. And this realization, is driving the shift of marketers from intrusive to contextual marketing strategies. Customers receive hundreds of messages each day, across channels, from businesses of all types, making it impossible for them to even open every message, let alone read it. In such a scenario, to generate customer interest or engagement, it’s imperative for marketers to deliver personalized and contextual customer communication. However, while personalization can be achieved through research about customers’ profiles, personas, habits, and preferences, to gain customer context we require much more advanced technological capabilities –data analytics.

In today’s situation, where customers do not shy from switching brands, and are extremely vocal about their positive as well as negative experiences with brands, marketers can’t risk their brand image by relying on intrusive, spray and pray sort of marketing tactics, that can at times be very annoying. Context makes your messages relevant, resulting in better customer response rates. The other day, I was trying to book an Uber drive, and a message popped up on my mobile phone from one of the popular payment apps, alerting me that I had almost exhausted my data usage. It also had a promo code offering some cashback on data recharge. Now, this is a contextual message, that triggered immediate action. Not being connected to a Wi-Fi network, I needed mobile data to continue booking the cab. This kind of contextual marketing – wherein a business delivers the right message, to the right customer, at the right time, through the right channel – requires real time customer intelligence.



Further, interconnectedness of the multiple channels a customer uses is another key factor that impacts the customer’s experience with a business. If I have submitted a support request to a business through a web form, and as a result I receive a call from their support team, I do not expect to narrate the same story on phone which I have already detailed in the web form. I toggle between channels, but expect a unified experience across all these channels, because it’s not the channel, but the brand that I’m interacting with.

Traditionally, marketers employ analytics to analyze historical campaign data and identify patterns, recognize preferences, derive customer insights, and use this intelligence to improve future campaigns. But, contextual marketing relies on advanced analytics to derive insights from customer interactions as they happen. Streams of data – structured and unstructured – including social media feeds, news feeds, emails, online purchases, call center logs, etc., flow into the analytics engine, which processes this data to create a 360-degree view of the customer. This view is unique to each customer and keeps evolving with time. It allows marketers to track each customer’s journey and identify triggers that motivate desired action at each step – from awareness to purchase, and beyond. Moreover, it also allows customers to move seamlessly between channels, or devices, throughout the buying cycle.

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Advanced active and predictive data analytics capabilities, enable marketers to weave context into every customer interaction across different stages of the buying cycle. This leads to better engagement, enhanced customer experience, better conversion rates, and higher retention rates. Having said that, it needs to be understood that contextual marketing is not about employing the most expensive analytics tools. The level of maturity of the analytics capabilities required by a business is also contextual. It depends on the nature of the business, the ecosystem in which it is operating, and a lot of other factors. Any decision in this regard warrants collaboration between the CMO and the CIO to perform a thorough assessment of the requirement, and come up with the most viable solution.



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