For the past few years there has been an urgency for organizations to transform into digitally-driven businesses. Because more than 80% of customer interactions happen through the web or a mobile app, marketing organizations have been center stage in the first of many projects to facilitate digital transformation such as revamping brand experiences, optimizing websites and performance, developing mobile apps, and so on. To support these initiatives, a myriad of platforms and tools were also introduced to the market to manage the automation and analytics of it all.
When trying to piece strategy and technology together, marketing teams are hitting roadblocks when it comes to data collection and analytics. All it takes is one look at the platform diagrams from the 2017 MarTech Stackie Awards to see that there’s a specialized marketing tool for almost every tactic in the funnel. A majority of the tools also have proprietary methods for collecting information to review performance. This hyper-specialization often means that marketers have a siloed and shallow view of their analytics. While “shallow” is great for speed in making guided day-to-day decisions, it is counterproductive when trying to determine what the single source of truth - or "golden" record - is to understand their customer analytics and what real improvement for the business means.
Interact With Customers Through New Mediums
Consider any social media platform use of machine learning to predict who will interact with certain ads. Now imagine your own organization trying to predict customer interactions by relying on its own business data. Internal marketing data, being rich in proprietary audience behavior and interaction data, will be critical for aggregation with third-party and operational business data to predict marketplace trends for your messaging and products.
This is where CMO and CIO organizations need to be purposeful collaborators. Getting insights from big data initiatives call on tactics such as machine learning, artificial intelligence, and augmented reality to name a few. IT teams have the platforms to provide the management and governance around ingested data from all sources to support a self-service data catalog back to the business. Marketing teams hold the keys to providing the human-centered aspects of unleashing the potential of master-level insights.
Explore New Data Products
“Data as a product” is another phrase that yields buzz and promise for new opportunity in a digital-centric world. Consider workout clothing with embedded sensors. By creating clothing that collects human performance data like body dimensions, heart rate, hydration levels and other physical information about a person during a workout, that manufacturer obviously has massive amounts of data. Although the primary purpose of this data is to make it so incredibly useful to their customers that said customers will buy more gear so as never to have a sensor-less workout.
The beauty of this data is in what the manufacturer hadn’t intended to collect through these sensors. In this mass of human performance data are the body measurements of every customer who wears the clothing. This manufacturer now has the potential to remove personal data and package the balance of it into averages of ages, genders, chest size, waist size, and other body dimensions.
The unintentional act is the perfect example of how a clothing manufacturer's own data can work together as both a disruptor and a catalyst for a new data product that this manufacturer might never have intended.
Collaborate Across Organizations Through Data
When an internal big data effort is designed to collect data for all departments into one main repository, internal business disruption is possible. Consider a strategy such as predictive subscription models or account-based product pricing. By aggregating collective client interactions with your brand, current revenue and profit projections, and third-party data, it is possible to transform and mine this data to provide right-time pricing estimates that match marketplace demand with the profitability trends of your business
This scenario isn’t possible unless there is a way to bring your marketing data (think web logs, automation statistics on certain messaging, etc.), client success data, sales and accounting data together behind the scenes.
And don't forget the most important part: When marketing data is ingested to a central repository, it can be used with other internal system data to influence how employees serve your most valuable resource - your customers.
Each of these scenarios makes one thing clear: Big data initiatives are a “whole business” initiative and the CMO organization must dive in head first. The CIO organization might own the tools and methods for production, but they are doing so with the objective of being able to take data from customer-centered organizations, align it with internal operations data to provide an efficient and useful data repository. This is why marketers must make it their business to align with their IT team to ensure that marketing data a key differentiator in their data-powered business.
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