2020 brought about a sea change in the way brands interact with their users, how users respond to these communications, and how changing consumer priorities have forced brands to optimize their day-to-day business operations. Businesses were forced to expedite a decade’s worth of digital transformation in a matter of days.

As more and more users come online to transact, consumer brands are looking for ways to humanize and deliver meaningful customer experiences at scale. Today, users demand a unique, engaging, and tailor-made experience at every stage of the lifecycle. For instance, doesn’t it feel amazing when Netflix recommends the shows and movies that perfectly fit your mood and interest every time?

This shift in consumer behavior has pushed businesses to rethink their engagement strategy and focus more on hyper-personalized and empathetic engagement.

To make a meaningful impression on customers and gain a distinct competitive advantage, it is important for consumer brands to build and deliver top-notch consumer experiences. This is when hyper-personalization comes to the rescue!

The Need To Adopt Hyper-Personalization

- 91% of consumers say that they are more likely to view items that are recommended based on information they've shared with the brand*. It’s clear that hyper-personalization helps brands to aid customers with faster decision-making and fosters deeper relationships, thus driving retention.

- 82% of marketers have reported an increase in open rates through personalized campaigns as compared to generic campaigns*. Safe to say that hyper-personalization has the ability to boost the ROI of your engagement campaigns.

- Hyper-personalization can reduce the acquisition costs by as much as 50% and increase the marketing spend efficiency by up to 30%*.

Marketing Automation Enables Hyper-Personalization

The rapid demand for hyper-personalization gave the much-required motivation to marketing automation solution providers to grow and expand their products to create one holistic solution.

Responding to changing consumer behaviour requires an ability to leverage customer data at the most granular level. This helps you understand who your audience is, what they are looking for, and what drives them to make buying decisions.

Collecting customer data at every touchpoint enables you to build unified user profiles across the customer’s entire buying journey. And target each customer with hyper-personalized engagement campaigns for maximum conversions.

However, achieving hyper-personalization at scale requires the technological capabilities of a marketing automation platform. A full-stack marketing automation platform mainly consists of 4 discrete layers: the CDP (Customer Data Platform), the Personalization Engine, the Engagement layer, and the Campaign Orchestration Engine

The Customer Data Platform collects and organizes real-time data across a variety of touchpoints. And build unified customer profiles by integrating data from a host of first-, second-, and third-party sources including website or app behavior, email and social media activity, etc. The 360-degree customer view helps you get the insights you need to better understand your customers and improve individual targeting.

The Personalization Engine adds a human touch to your marketing communications. The engine derives information from the CDP and the Recommendation Engine to create tailor-made messages that feel unique and specifically crafted for individual users. Thus driving user engagement and retention.

A great example of a consumer brand that has achieved incredible growth trajectories with hyper-personalization is Spotify. With over 5 billion streams, their Discover Weekly feature has been a big hit. It studies individual music choices and cross-analyses this data with the preferences of other users who listened to the same songs to create a highly-personalized playlist for each user.

Another good example of hyper-personalization is Shaw Academy - a leading online education platform that boosts its revenue by 25% through hyper-personalized engagement campaigns. These campaigns are hyper-personalized based on student attributes like Country, UTM parameters, and more, resulting in higher engagement.

The Engagement layer essentially takes care of channel management and user analytics. It helps you identify the right engagement channels that a user is available on, deciding the best time and channel to reach your users, and creating an omnichannel user engagement strategy that boosts conversions. For example, Go-MMT, India’s leading OTA brand, boosts its hotel partner engagement by 20%. With the help of a multi-channel marketing automation tool, InGo-MMT was able to engage with the hotel partners on their preferred engagement channels like SMS, Email, Mobile, and Web Push. Thus driving engagement and revenue.

The engagement layer is also responsible for insights and analytics that helps you create and course-correct engagement strategies to deliver optimum results. Take A/B testing as an example – you can run multiple campaigns on smaller test groups and based on their responses can automatically trigger the best variation to the rest of the audiences.

And finally, the Campaign Orchestration Engine takes care of the automation part of your campaigns. You can set up rules, define conditions, and chalk out the entire customer journey. It helps you automate your funnel optimization process with pre-set communications to be triggered as the user moves along the sales funnel, thus driving conversions. For example, Zivame, an online lingerie retailer, uses Web Push & Web Pop-ups through Journeys to increase conversion by 20%. The communication is hyper-personalized using attributes from the user’s behavioral history and profile details.

DSP BlackRock, a large mutual funds company, uses hyper-personalization to increase engagement through emails. The FinTech brand leverages data like user profiles (name email, age, and demographics), user events, screen data and third-party data to deliver dynamic email communication at scale.

The journey Designer ties the CDP, Personalization Engine, and the Engagement layer together to create one holistic user engagement and retention platform.

Additionally, it saves the human effort of manually creating dedicated campaigns for each micro-segment, which otherwise would take insane man-hours.

Final Thoughts

Today’s customers expect brands to speak to them as individuals and reach them on their preferred engagement channels with relevant communication. Conventional marketing processes will no longer help you achieve the next level of growth for your organization. A robust, data-backed, hyper-personalized marketing strategy can help you address most of your challenges. A technologically sound marketing automation platform can help you:

1. Maximize revenue generation through data-driven content generation, granular product targeting, and individualized product pricing

2. Reduce the cost of acquisition and retention through workflow automation

3. Elevate your customers’ experience through in-moment customer journeys, real-time customer segmentation, and dynamic user-specific screens on your app/website.

Hyper-personalization is the key to continued business growth for consumer brands, in 2021 and beyond!

The author is Avlesh Singh , Co-founder & CEO, WebEngage