- Every action consumers take helps businesses generate a ‘Code Halo’
- Halo data and predictive analytics make for a very powerful combo
YOU are on a first date. The conversation will likely centre on learning more about each other’s personality, habits and preferences, so you can assess if a second date is in order.
Wouldn’t it be great if you could skip ahead to getting an accurate prediction on your long-term compatibility without having to go through the formalities?
What possibly holds a simple answer to this is predictive analytics.
Of course, not all analytics are created equal. It takes a unique kind of analytics to reveal behavioural realities and ensure optimal outcomes.
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For businesses, a robust understanding of consumers’ preferences and habits can go a long way in building meaningful and long-lasting relationships with them.
In the end, isn’t brand loyalty what all businesses crave?
Any good relationship has a degree of intimacy. This means that the more you know a person, the more effective the conversation.
In a world gone social, the most compelling narrative to advance a business relationship isn’t always a ‘buy’ message; it’s often a value exchange.
Casting a halo of light on the consumer
Increasingly, every action consumers take – be it clicks, swipes, comments and posts – helps businesses generate a unique virtual identity for each person.
This forms a halo of code – a ‘virtual self’ that surrounds each one of us. The data that accumulates around people, devices, and organisations can be very powerful and rich with meaning and insight.
Like a fingerprint, each person’s halo is unique. And therein lies its power.
This halo of code approach – which we call Code Halo – puts business owners on the fast track to digital success.
The powerful combination of halo data and predictive analytics enables businesses to better understand each consumer and to create new consumer intimacy and immediacy models.
Indeed, the best predictive analytics solutions can help shape and personalise product messages by decoding personal halos to such a fine level that they can anticipate shopping patterns by cross-tabbing participants in a hashtag campaign with product purchases.
Achieving long-term consumer relationships
Predictive analytics can help businesses build and sustain long-term consumer relationships, and more importantly, keep them engaged with their brand for a lifetime.
Here’s how to do it in four simple – but not necessarily easy – steps:
Step 1: Change how you engage with consumers
Businesses should know that marketing has moved from 15- and 30-second commercials to a 24x7 communication cycle, yet most companies are stuck in the past.
Making that shift is key to realising the uncharted business potential of one-to-one consumer relationships.
Businesses need to start making the cultural shifts necessary to evangelise the power of connecting with individuals, while also examining how they can respond in relevant ways to always-on consumers connected across multiple channels.
Step 2: Stop working in silos
Break down brand silos by examining how consumers might engage with the entire portfolio of brands.
Why, when, where and how might shoppers purchase across all of an organisation’s brands? Tap the halo of code approach by distilling transactional and interactional data correlated with products to really figure out the consumer’s needs, wants and desires.
With this, business owners can see where markets are heading and what products need to be developed or refined, before consumers even articulate their preferences.
Step 3: Manage the brand and relationships together
Managing across the organisation’s portfolio of brands requires focus. Businesses should assemble a team to carry out this all-important task.
To ensure the integration of brand planning with relationship management, assign a customer relationship expert to each brand.
Consumers often make choices between parity products and services based on the perceived customer experience. This allows businesses to stand out from their competition.
Step 4: Deploy a predictive marketing analytics engine
Successfully executing relationship marketing strategies and tactics requires an advanced understanding of consumer behaviour via analytics and predictive modelling of consumer data.
Today, social media and location-based messaging provide businesses with more data than ever on potential leads and customer preferences.
Putting all the sources together allows marketers to gather valuable insights. As a result, campaigns can achieve higher conversion rates, and budget and resources are more effectively utilised on those most likely to buy.
No time like the present
Theodore Roosevelt once said, “Nothing in the world is worth having or worth doing unless it means effort, pain, and difficulty.”
While the steps described above may seem quite simple, they aren’t necessarily easy to take, given existing infrastructure, standard operating procedures and the traditional thinking about customer relationship management that still prevail in many businesses.
However, businesses cannot afford to put them off.
The power of predictive analytics tools today, and unprecedented access to consumer data, mean that businesses can begin to create lasting one-to-one relationships with consumers for sustainable future.
It is important to take the first step.
Jayajyoti Sengupta is Asia Pacific head at Cognizant Technology Solutions
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