The future of marketing analytics: How can brands better understand their customers?

The future of marketing analytics: How can brands better understand their customers?
Allen Bonde is vice president of innovation at OpenText.

(c)Сергей Хакимуллин

Today’s tech-savvy consumers demand smarter apps that inform them with helpful information, connect them to tailored offers or experiences (or peers) and ultimately motivate them by using data to drive behaviour – like the best fitness trackers. This means that for marketers, good campaign design increasingly starts with the data, and in the near future will be about the interaction “device” rather than the channel or place.

It also means that despite all the hype around social media and mobile and new technology for ad and message targeting, the story really needs to start with the customer. Only by thinking of their journey, and what data is available to inform, connect and motivate them along the way is it possible for marketers to understand the needs of consumers in the new digital world. The end goal? Better awareness of market dynamics and customer preferences so modern marketers can deliver meaningful, personalised insights on the app or device of their choice, and fully engage buyers at each stage of their journey with the brand.

Even better, the good news is that marketers are not starting from scratch. Marketers already have lots of data history, tools and approaches to build on, and research by McKinsey reveals that companies which put data at the heart of their marketing or sales decisions improve marketing ROI by 15-20 per cent. The challenge lies in being able to bring the power of data to life, and turn information into actionable insight that everyday campaign managers and end-consumers can use without a degree in data science.

Visual analytics for marketers

Today’s marketers are faced with the challenge of rising volumes and varieties of customer information. The recent growth of disruptive technologies – such as new mobile devices and the Internet of Things – has increased the number of customer touchpoints and given marketers access to alternative sets of small and fast data that they need to extract value from. And these options are only going to increase as shipments of wearable devices are expected to surge this year (up 173%!) according to market watcher IDC. To tap the potential of these new sources and devices, marketers need to rely on new techniques, such as data visualisation and advanced analytics, to put data into context.

With the explosion of new types of data available today, marketers who don’t have the tools to easily gather, “blend” and explore it will be at a disadvantage. One of the key ways for marketers to make sense of all of this is gaining a “360 degree” view in some visual form, which allows them to mine and gain insight into the data, draw conclusions and build “smart” segments, profiles and behavioural models. Yet the majority of marketers today do not have a data scientist background, so the ability to easily understand and socialise market data is crucial if organisations want to capitalise on the creativity of the marketing function, without requiring an understanding of complex mathematical or statistical algorithms.

Predicting what’s to come

Once marketers have access to all their customer data in one place, then it’s possible to focus on the future and start to predict what’s likely to happen next. Indeed, the most exciting aspect of marketing that’s emerged with the proliferation of big and small data is the idea of becoming truly “data-driven.” Thanks to new tools that are more powerful yet easier to use, predictive analytics is moving from the labs of data scientists and into the business function. In the hands of these users, predictive analytics is helping answer questions and predict consumer behaviour to enable much more targeted and “agile” marketing. For example, while traditional BI can tell you how many telco customers have churned in a year, tools like a big data analytics appliance can help you identify which customers are most likely to churn, and what offer may keep them from leaving.

With new predictive analytics solutions giving rise to a new class of data-driven marketers who have more business and market knowledge than deep analytics know-how, the ability to predict outcomes and operationalise big data insights on a daily basis can now be a key marketing asset for businesses. In fact, the latest all-in-one tools enable marketers to bring together large scale transactional, social, web and third party data into one place, and analyse it to understand relationships, preferences and future behaviour. Armed with this information, marketers can keep up with their customers’  increasingly demanding expectations while delivering new business insights that drive better strategic decisions.  

When coupled with data visualisation techniques that deliver insights to the masses (including customers), we can start to see an end-to-end analytics process emerge. First we use data to better understand our market and our customers to identify buyers and ideal offers. Then we engage these buyers with data-driven visual information like alerts or infographics. How they interact with these assets – say via their mobile device – creates new data points we can monitor, which allow us to refine our models, and deploy the next, more targeted campaign assets, and so on.  This iterative process is critical to not only gaining key competitive insights, but also quickly adjusting to the whims of today’s increasingly distracted consumers.

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