Big Data: There's too much stinking thinking from CMOs
Right now, CMOs often use bits and pieces of Big Data to just do more of the same, more often and more aggressively. But it can do more.
The internet has become a very powerful engine for discovery. That’s why Econsultancy’s Marketing Budgets 2013 report had 71% of respondents say that they plan to increase their digital marketing budgets this year. But CMOs have to ask a very basic question: what is the most effective way to “digitally market” in 2013?
Many companies point to Big Data as the answer, but in Gartner’s Big Data, Bigger Opportunities: Investing in Information and Analytics report, Doug Laney, research VP at Gartner, explains that the means for actually deriving and understanding value from data is still in its infancy: “Organisations have increased their understanding of what big data is and how it could transform the business in novel ways. The new key questions have shifted to 'What are the strategies and skills required?' and 'How can we measure and ensure our return on investment?'”
Now, there’s a distinct difference between just acting on data and actually being good at acting on data. In the years ahead, that’s what will make a company’s marketing programme succeed or fail.
The missing component: personalisation
Right now, CMOs often use bits and pieces of Big Data to just do more of the same, more often and more aggressively. Yes, you can launch a campaign based on a big list of customers pulled from the latest BI report, but do you really know that every single customer would be interested in the offer? Without context, you may just annoy your audience with an untargeted, unhelpful marketing message.
As the online world is flooded with content for every niche, consumers themselves are more attracted to marketing that’s crafted for their specific interests and behaviours. In just a few minutes, they can find the right solution for their situation and skim ten different reviews. Likewise, they can talk with each other and to the company over social media channels.
From websites to apps to social media, customers expect personalised, relevant content. Companies that continue to rely on a fire hose approach for marketing are going to get drenched. Customers have little patience for generalised marketing and they’ll punish the companies that fill their email inboxes or interrupt their browsing experience with irrelevant content.
Big data is the resource that businesses need to solve this problem, but the tools and strategy to use it are usually missing. This needs to change, because predictive analytics is the key to marketing in this new world of custom content. If you can analyse Big Data and figure out the behaviours and trends that make a customer more receptive to one marketing message than another, ROI is going to improve.
So how can CMOs learn to categorise this behaviour in a way that makes sense, so they can adapt their marketing to all this new data?
Organising the chaos into stages
When businesses start using analytics software to parse big data and identify trends among customers, it’s important to pinpoint where each customer is in the buying cycle. That’s when they can think about what marketing message will resonate most and what kinds of special offers or product upgrades will be attractive to them.
Essentially, these behaviours fall into three different stages, the “3 P’s:”
- The Past View is static and reflects the individual’s “path” to the present state. These are the experiences that have led them to the here and now: transactions, interactions, complaints, and marketing behaviours.
- The Present View is dynamic and reflects context. It’s always changing. What channel is the customer on right now? How do they feel about your business, what’s their intent, and where are they? The data points here are customer sentiment, influence, location, and channel.
- The Predictive View builds upon the past and present to show the trajectory of the customer. This is how you evaluate where the customer is likely to go— are they a retention risk? Is there an opportunity for an upsell?
Lifetime value, risk, profitability, selling opportunities, and retention are all fundamental here.
The first two P’s are foundational to the third. When you know the past and the present view of a customer, it’s possible to use big data to predict what’s going to happen next. In turn, that allows CMOs to launch marketing programs that are custom-tailored for a data-based prediction on future buying habits.
Using Big Data to gain customers, not lose them
Big data has opened the door for businesses to supply customers with the custom content they now expect. Instead of targeting a standard buyer persona or a market segment, CMOs can use analytics to drill down to the individual level and answer some serious questions.
How does the customer feel about your company? About your products? What trends have you seen that indicate that this specific marketing message will be effective?
We are in an age of unprecedented personalisation when it comes to both content and communications, and businesses need to catch up. Customer behaviour is changing all the time, in large part thanks to the internet. Rather than a trend that develops over years, a single Tweet or review can suddenly cause a ripple effect that takes place inside of a day, pushing customers to a competitor or making them think twice about upgrading. The companies that can use big data to monitor these trends and be there with solutions the moment they happen are the ones that will pull ahead - building business and customer relationships that last.
Kieran Kilmartin is marketing director, EMEA, at Pitney Bowes Software.