Unlocking Consumer Parallelism through Analytics
Unlocking Consumer Parallelism through Analytics
Being a middle school student is not as simple as it used to be. Today it is all about group projects, hands-on experiments, and research-intensive assignments. And however tech-savvy most children are these days, it’s up to the parents to provide a little support when it comes to internet research on suggestions, ideas, and information beyond the textbook. In fact, as the father of a young boy, a lot of my own Google search terms are along the lines of: ‘scale model of the solar system’, ‘molecular structure of hydrocarbons’ and famous historical characters like Lala Lajpat Rai and Nelson Mandela.
When I’m on LinkedIn, it’s a different story. I follow groups and influencers in the martech space and catch-up on the latest, global thought leadership stories. I also spend some time following rising stars in my professional domain who may be ripe to recruit for my organisation. On Facebook, my activities are mostly related to keeping in touch with family and friends.
This is the story for a lot of us. My multiple personas, like other customers, are just different tabs on my browser, but my behaviour and preferences on these different platforms, are worlds apart. Like many others, I too am the definition of ‘Consumer Parallelism’! My myriad avatars on the digital landscape are spread across platforms and devices and sometimes even simultaneous. So how does a marketer cater to customers with such divergent digital avatars?
It’s not easy, for sure. The age of Consumer Parallelism is a sizeable challenge for marketers to understand this ever-changing customer. Customer journeys are no longer sequential. They are ‘fluid’, across multiple channels and touch points, and at the customer’s pace. To create positive and compelling customer experiences as a key enabler of growth, marketers need to focus on going beyond a mere transactional relationship and towards transformational, memorable customer experiences.
Track to Crack the Customer Sentiment Code
The first step to determining customer sentiment is to track what the customer wants v/s what marketers think they want. The needs and expectations of your millennial customers are very different from your Baby Boomers. They also act differently online and offline. This requires marketers to deploy different tactics to engage with them. Marketers need to engage with the customer on a real-time basis with the right content, and to meet him at his point in his journey. This trail-tracking sniffs out and deciphers the body language of the customer and provides deep, behavioural insights into their multi-dimensional personas.
A Data-Driven Journey
Consumer Parallelism also means the already vast volumes of customers data, have become more complex. Marketers now need to make sense of raw stacks of scattered data generated by the CRM or by vendors and across digital channels and platforms. Of course, every challenge is an opportunity in disguise, so the data explosion is also an opportunity to architect a 360-degree view of the customer. With a nuanced understanding of the customer’s needs, at each stage of the lifecycle and across platforms, marketers can create highly personalised and content-driven engagement and retarget them with communication in real-time to drive revenue growth and loyalty.
But, the spanner in the works – lack of data readiness and structure, incomplete data sets, security concerns, disparate data points, compound the obstacles to marketing excellence.
Although Consumer Parallelism renders demographics and segmentation ineffective or inadequate, a centralised data mart, created by data integration specialists, can summarise transactional, behavioural and demographic data. This summary-level data can then be linked to a marketing automation solution for to determine the customer’s responses to marketing campaigns, through a unified view. This offers an encouraging glimmer of hope to marketers. Next, integrated analytics can step in to unlock the answer to the marketer’s burning question: ‘How do I view my customer’s data and compare it with the performance of my marketing campaigns?’
Data-driven marketing is the ask and integrated analytics is the answer. Rapidly changing customer behaviour means that businesses can only drive growth through a unification of the Chief Data/Information Officer (CIO) and Chief Marketing Officer (CMO) roles. This results in a merging of customer analytics, which delves into customer behaviour, and marketing analytics, which measures the ROI of marketing efforts. Merging customer and marketing analytics will be the starting point to effective and truly data-driven marketing.
To tackle Consumer Parallelism, good data, that generates value for different types of analytics, like predictive analytics, can go a long way towards addressing the needs of multi-faceted customers. Armed with deep insights, marketers can leverage analytics to see a reduction in churn rates and a rise in cross-sell rates. These empowered marketers, who can track and act on customers as they flit across platforms, exhibit parallel behaviours, and interact across multiple devices, can in turn provide perfect, timely, and extraordinarily effective content.
The original article was published by Analytics India Magazine.
- App Engagement
- App Push Notifications
- Artificial Intelligence & Machine Learning
- Campaign Management
- Email Marketing
- Email Security
- Growth Marketing
- In-App Messages
- Marketing Automation
- Mobile Marketing
- Powering Smart Conversations
- Product Update
- Push Notifications
- Tech startups
- Web Engagement