How to Use Data-Driven Marketing to Boost User Engagement [Webinar Wrap-up]
Reading Time: 5 minutes
Imagine your market to be a sea that’s sprawling endlessly in all directions. Will you let your business ship cruise to the whims and fancies of market winds? Alternatively, will you navigate it with purpose towards a specific destination?
To navigate your business to a specific destination, you need a compass – which is data. Data enables you to focus on the right route that works and helps you scale for maximum impact. In a way, it is like looking at your business performance through a magnifying glass. Data is the cornerstone upon which successful decision-making rests.
Bonus Content
👉 Beginner’s Guide to Omnichannel Marketing for 2021 [Download Ebook] 👉 Retail Strategies and Omnichannel Engagement Frameworks [Download Ebook] |
Anjan Bhojarajan and Pooja Ravishankar are two such business leaders. Pooja Ravishankar is the Head of Category Marketing with BigBasket who spearheads both online and offline channel marketing. She successfully built the analytics database platform and recommendation model that powers BigBasket.
Anjan is the VP of Growth & Head of Product at HealthifyMe. He’s been part of the company’s growth story from 2 Million users to 10 Million users on their app. A webinar that brings together these two experts requires a fitting moderator. Akshatha is the content lead of MoEngage, an intelligent customer engagement platform. She helps MoEngage grow by leveraging the power of evergreen content.
The theme of the webinar was “How to use data-driven marketing to boost user engagement.” If you missed to tune in to the webinar, you could always take a look at the recording below.
Even in a dynamic and people-centric function like marketing, data is all-important. The business leaders today rely on data as their primary tool for both short-term and long-term decision making. You can read all about it here.
If you are someone who enjoys a quick read, what follows is a shortened version of the webinar’s conversations.
At Big Basket, Data is The New Emperor
Big Basket is India’s largest online grocery brand. With more than one million monthly customers and eight thousand farmer connections, BigBasket is a disruptor in the Indian grocery space. Handling the marketing of such a large brand requires a lot of planning and analytics. There is no room for guesswork. Pooja believes that data takes the guesswork out of marketing.
From Amazon to Zappos, every company on this planet collects data. They collect petabytes of data not to store them aimlessly on their servers, but to analyze them and to pick up patterns, averages, and insights that can drive the business forward. Data-driven marketing can turn even a casual window-shopper into a loyal customer.
Pooja shared with us some data-driven marketing techniques that Big Basket leverages to deliver 5-star customer experience.
Every marketer has two priorities:
BigBasket’s Secret Ingredient to Customer Retention
During the webinar, Pooja broke down the concept of Smart Basket — a Machine Learning (ML) based algorithm that predicts what the customer’s next purchase based on buying patterns.
Machine Learning is a data-driven system which sifts through vast amounts of data to arrive at predictions or recommendations. Online retailers like Big Basket leverage it to pick insights and offer product recommendations to customers. For instance, the ML-based algorithm enables Big Basket to provide product recommendations that customers might need to replenish.
When a customer visits the app, their previous order quantities and order dates are related to consumption patterns to estimate their needs on the particular need. This helps in reducing the time taken for shopping, as well as boost user engagement.
How Big Basket Prevents ‘Recommendation Fatigue’
There is one long term behavioral shift that product recommendations might induce into the customer’s buying patterns. They become blind to new products as they do not have to go a discovery spree, leading to what’s called the ‘recommendation fatigue.’
To ensure that customers have a healthy mix of recommended products and new products, Big Basket uses an item-item collaborative filtering system. Similar to Smart Basket, this is also a system that relies heavily grounded on data science. The system ensures that users get introduced to new products based on their recent shifts in buying patterns or based on the group buying patterns of similar user personas. The system also incorporates external data points like annual consumption and preferences to enable customers to discover new products.
These two systems, combined with personalized and targeted messaging of offers, enables Big Basket to deliver a 5-star customer experience.
As a bonus to her presentation, Pooja also listed down the five things that a marketer needs today to perform at their best:
HealthifyMe’s Global Growth Story is Data-driven
HealthifyMe is India’s largest and also most loved health app. The app operates in 3 countries — India, Malaysia, and Singapore. It has maintained a 4.6 app store rating and also managed to get into the most favorite apps list consecutively for three years. The health app even managed to scale from 2 Million users to 10 Million users in just two years. How did HealthifyMe pull it off? Anjan broke down how HealthifyMe dives deep into data to power its growth story.
HealthifyMe starts populating data about a user right from the time they sign up. At the onboarding stage itself, personal health details like weight, height, health issues, fitness goals, etc. are collected from the user. Based on the data collected, the user is offered personalized content and a health plan or assigned a personal coach to reach their goals.
Given the geographical spread and cultural diversity of its user base, it would be quite difficult for any app to cater to personalized suggestions. HealthifyMe solves this problem with the power of data analytics. They unlock several data variables during the journey of the user which enables HealthifyMe to deliver precise and personalized content, food plans, and coaching instructions.
Hyper-personalized Health Training
HealthifyMe picks up variables like user location to match them to coaches from nearby regions. Thus, they can cater to users with regionally corrected diet regimes. Further, they also loop in daily feedback systems into the app. These systems inform the user of their calorie intake during the day, what they should, or they should not eat the next day, how to take the diet plan forward, how to stay motivated and so on.
Retaining Users with Content-goal Mapping
Anjan also explained in the webinar how HealthyifyMe turned to data to segment customers based on location and goals. Each segment and its goals were mapped to content through in-app feeds and notifications. Granular level personalization of notifications like — including the user’s name, use of emojis in the notifications, etc. also enabled HealthifyMe to create a connection with its users.
Final Thoughts
Digital savvy customers have tons of options. That makes customer acquisition and retention an enormous challenge for marketers. With data by your side, you can tackle the problem and even turn it into a competitive advantage. The success stories of Big Basket and HealthifyMe prove that. Having a data-driven approach to marketing can help boost your user engagement, as well as retain customers for a long period.