Feature
If Marketing Came with a Do-Over Option
One of my favorite movies is Groundhog Day where Bill Murray relives Feb 2nd (Groundhog Day) over and over again and everyone else except him experiences the day as normal. He gets to observe all the other characters, learning what they do, and he uses that to his advantage the next time the day repeats itself.
What does that have to do with marketing? As a marketer trying to convince someone to buy something (or just give you a business card), imagine if like Bill Murray in Groundhog Day you got multiple attempts at a conversation, where the customer has no knowledge of your previous engagement? Unbeknownst to the customer, you have seen how they behave and understand what motivates them to take action (or not), and you are able to "re-do" the conversation in a way where the outcome is what you desire as a marketer.
Do you think you would get more people to become interested in what you have to say and ultimately do what you want them to do?
Until time-travel becomes a reality or the world behaves like the fictional Groundhog Day, what's the next best alternative? How do you read between the lines of the millions of conversations a business or brand has with its visitors, prospects and customers to find those nuggets of insight that allow you to have more meaningful and convincing conversations with them?
Many would advise the use of data-driven marketing. The only problem is that what constitutes data is constantly being redefined, and traditional marketers are reluctant to embrace the new world of data driven marketing in the first place.
In his CIO Journal article “Don Draper has left the building: The Rise of Data-Driven Marketing,” Thomas Davenport discusses how marketers are under increasing pressure to show that money spent on ads, promotions and other forms of campaigns actually generates sales and revenue. But he also points out that in a Corporate Executive Board survey, 800 marketers at Fortune 1000 companies revealed that marketing executives depend on data for just 11 percent of all customer related decisions and only six percent of the marketers could correctly answer five basic questions about statistics. A Teradata survey of 2,200 marketers found that 75 percent of marketers said that they have difficulty in calculating the ROI on their data-driven marketing spending.
But what about the 360-degree view of the customer that marketers have been talking about for the past few years? It is time to break the difficult news: The 360-degree concept has lulled them into a false sense of security or accomplishment.
The truth is that looking back in time by tracking customer history only tells us part of the story, especially if the data sources are siloed. This is compounded by the fact that work teams and business groups aren’t sharing information and insights, and the analytics are not crunching real-time data. This provides limited insights into customer behavior, sentiment and experiences across channels and touchpoints. To remedy this, you have to consider the context of the current interaction with the customer to truly influence behavior.
A Multidimensional View of the Customer
Analyst firms and industry leads suggest that marketers move beyond the data-driven and 360-degree view of the customers in order to work from a deeper understanding of customer behavior and needs. This is called acquiring a multidimensional view of the customer.
The multidimensional view requires fast and agile analytics including predictive capabilities so marketers can deliver a real-time, relevant and personalized experience to their customers.
Sounds straight but it’s not easy, and here is why:
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- In most companies, marketing is handled by different groups that are organized by channel instead of by customer journey.
- Each group employs its own tools and strategies to communicate with the customer via that channel. Some of them use marketing automation tools while others rely on agencies that use their own tools.
- Using disparate tools either in-house or by agencies results in the data about customer conversations being captured in different systems, forming data siloes.
- The information that is being captured is a combination of structured data like transactional information, semi-structured data like clickstream URLs or search keywords and unstructured information such as Twitter posts, Facebook comments, reviews, positioning content, videos and images, web page content and more.
- The techniques and tools used to analyze all this information are inadequate because they do not provide insights or are too expensive and complicated to use.
- And most importantly: The sheer volume, velocity and variety of information is hard to manage and analyze. To highlight a few statistics from a 2011 article on big data (Big Data -- The next frontier for innovation, competition and productivity, McKinsey Global Institute), there is over 13 hours of video content uploaded to YouTube every minute, 30 billion pieces of content shared via Facebook every month and, staggeringly, more than 90 percent of the world’s data today was created in the last two years.
Discovering the Hidden Customer: The Convergence of Marketing, Big-Data and Analytics
Many marketing organizations at Global 1000 companies are attempting to solve this problem, but the techniques they use are still too expensive and time consuming, preventing them from realizing the full potential of using a multidimensional marketing approach.
More often than not, they are only dealing with structured or semi-structured data or by converting unstructured data into structured formats, losing a lot of fidelity in the process. Typically they rely on aggregating this data into large marketing data-warehouses, hiring a number of statisticians or data-scientists and creating/running models to understand customer behavior.
This can work, but it is very limiting and inefficient. Most of the models are built using statistical packages in SAS, R or similar tools. The models are built for very specific types of analysis and any changes can take weeks of additional work. Also, the time it takes for the models to run varies and in some cases can take as long as a few hours to complete. Because of this, the analysis cannot be applied in real time and so the prediction is only as good as the last time the model was run. This is like trying to drive a car while only looking into the rear-view mirror.
A classic example of this is the scenario where your favorite online retailer is recommending Barbie dolls for you because of previous purchase history, even though you are currently browsing LED TVs, reviewing comments on specific TV brands and watching customer videos related to TVs. How does one find this hidden customer amidst all the noise from the historical data that is being collected?
A Real Big Data Analytics Platform for Marketers
In order to find that hidden customer, marketers need tools that can analyze both structured and unstructured data in real-time at the scale with which it is being generated today (and even more tomorrow), and use those insights to predict customer behavior in the future. It is no longer about historical report generation.
Behavioral insight via segmentation is not just about clustering customers based on their attributes and conversion data. A marketing analytics platform should be capable of identifying your highest performing groups of customers based on the conversion data or KPIs that you care about, and should be able to give marketers the additional insight regarding which attributes are most influential towards the conversion.
Also, marketers should be able to determine which content viewed by customers performs best as it relates to conversion or meeting specific KPIs. These insights can then be used to determine who to target in the next campaign and what kind of content should be used for specific groups of people or even down to the specific individual customer. And the platform should be able to provide these insights in real-time so marketers or systems can act on it “in the moment.”
Better still, if these insights were directly actionable in the tools that marketers use such as marketing automation tools, CRM applications and content management systems, or if it could feed into contact center applications, marketers could act on insights from within the application they are using.
Is this the mythical unicorn for marketers? Is there where marketers get to be like Bill Murray in Groundhog Day? Is this even possible?
Yes -- it is possible. It requires bringing together content management, multichannel delivery, optimization, big-data information analytics (both unstructured and structured) and combining that with new approaches and mathematics to solve this at scale and in real-time. Most importantly, you need to have the right business processes in place to allow for easy data sharing between groups and looking at the whole customer journey, when using these tools for analysis.
Title image courtesy of Bahadir Yeniceri (Shutterstock)
Editor's Note: To read more by Sunil see Case Study: Five Companies Automate Marketing Processes to Impact Bottom Line
