Is there one definite way of engaging with the end-users? What data points do you use to gauge these decisions? Consumer engagement, when done incorrectly, is nothing but spam or inaccurate marketing. One way to navigate this puzzle is with analytics.
This recent discussion on improving user engagement through analytics is a goldmine of information. Ms Pooja Ravishankar, Category Head of Big Basket, Mr Abhishek Joshi, CMO of MX Player, and Mr Nitin Sethi, VP Digital of Indigo Airlines, share details on user engagement for their companies and the tricks of the trade.
As the saying goes, “What gets measured gets done.” This factor is valid for all aspects of a business and sets the basis to determine what data points one must measure.
One of the most valuable data points is a returning consumer. This behaviour helps to retain the customers and keep a check on the bottom and top line. Based on the nature of the business, you will monitor the consumers’ return between one and six months.
In the case of an essentials or e-com company, this number should be much higher. For example, commodities like fruits and veggies are needed by all households once a week. The shelf-life or necessity of your products can determine the return rate of your end-users.
“We check how much is a person buying in a month/year and how many categories does this person buy across a lifetime,” says Pooja Ravishanar from Big Basket. The data on user behaviours depends not just on the transactions; it’s also about the variety. A more loyal user will browse a more significant number of categories.
If you are a company that frequently changes the offering of your platform, like in the case of an OTT platform, the return of the consumer will determine a vast number of details. For example, you can understand what offerings are valuable, which UI and UX changes are better received much more.
According to Abhishek Joshi of MX-Player, this information will also help the brand create content. The current nature of engagements should be the basis of new content.
Gathing data on a user might be the more accessible part of this task, but turning data into useable insights is where the real challenge lies. Analytics is not an overnight process, and the leaders of all organisations will be in agreement.
Studying data is one of the elementary steps to better growth. If done incorrectly, it will only lead to negative results. For example, after just three weeks of its launch, MX-Player became the second most popular OTT platform. This success was only possible since all the data previously collected was used spot-on.
“A company cannot also depend on a one-size-fits-all solution,” said Nitin Sethi of Indigo Airlines. Every user will demand something different from the platform or website. The brand must understand the nuances of the customer and make the value proposition relevant to each segment.
To state an example, Big Basket created a “Smart Basket.” This tool checks a users’ purchase history to suggest items that have probably run out at their homes and kitchens. The basket will constantly offer options based on the user and not just product popularity.
Confused? Consider the example of garlic and meat. Many communities in India do not buy these products, but they are still best-sellers overall. This difference forces a brand to study the user behaviour and purchase history before suggesting and not depend solely on product popularity.
A consumer can discover the product from various sources: search engines, third-party sellers, or your own platform. The aim is to bring them to your own platform ultimately. This allows brands to use the insights better.
A company should be mindful to engage with a user and not spam. In the words of Nitin Sethi: “Don’t cross the line between being intrusive and providing great user experience.” You do not want to push your users against a wall with engagements but cherry-pick opportunities.
“Have a data-driven culture in the organisations,” says Pooja Ravishankar. When all decisions are made based on the data, only then can a company find success. A company or person should know how to look at data correctly and not apply a personal lens.
If we consider the engagement from content, 60% of consumption comes from short-form content. “People who search online have always come for long-form content,” says Abhishek Joshi. “We can use this as a rule-of-thumb and create content accordingly to encourage actions.”
Lastly, we must address how does someone achieve these data points that we speak off. There are mainly two ways to do this:
Additionally, a brand cannot assume data. A pool of data and insights is not iron-clad. Brands have to perform A-B-Testing on the insight on a small group of users or a minimal number of attributes.
If we consider the ideal use of analytics for better engagements, we can break them down to these valuable learnings:
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