Welcome to the third edition of our blog series exploring consumer brand relationships. This time, we’re mapping consumers across platforms, using data lakes, and looking into emerging marketing ops. Don’t miss the earlier editions of this blog series: Brand Loyalty, Brand Disloyalty and Brand Habits and Emotional Brand Loyalty.
We touch our phones over 2,000 times a day, more if we’re heavy users. We may do this while we’re watching TV, working on our laptop, and/or shopping on our tablet. With the average consumer utilizing 3.64 connected devices daily, ‘identity measurement’ and ‘customer journey mapping’ has become a hot topic.
Tracking consumers across devices
It’s estimated that 50% of e-commerce transactions worldwide involve a cross-device purchase journey. How can marketers track, communicate, and convert people when they’re not on a linear path of consumer awareness, consideration, loyalty, and advocacy?
Marketers who are trying to follow their ideal consumers across device platforms can make some determinations based on IP addresses and browser settings, or, ideally, through logged-in accounts like Gmail or Facebook. Browser cookies alone won’t capture all the info needed for proper analytics.
Google and Facebook are predicted to become the leaders in online-to-offline (O2O) attribution, because they are most able to identify user behavior and events that will lead to desired outcomes. However, here’s the bottom line: it’s not easy for anyone to get a clear and concise picture of what’s going on presently.
A 2016 survey by Econsultancy looked at the ability of North American companies to match customers across multiple devices. 75% responded this was a ‘top digital priority’, but only 14% felt their company had the ability to effectively do this.
KPIs, insights, and ‘Micro-moments’
Major brands and advertising platforms are trying to understand how to turn an ever-increasing volume of data points into timely and relevant insights.
Lisa Gevelber, Vice President of Marketing at Google, describes the need to capitalize on “micro-moments”, when “someone is looking to learn something, go somewhere, do something, or buy something.”
Consumer expectations are high. Many expect companies to know what they want or need, where they’re physically located, and serve up relevant content.
Companies need to:
- Identify consumer micro-moment needs
- Formulate a strategy to respond to those needs
- Be able to act quickly
Case Study: Netflix
Peter Fader, Professor of Marketing at the Wharton School of the University of Pennsylvania, provides an illustrative case study using Netflix. Netflix wanted to create a series that would increase loyalty with existing customers they deemed desirable. Additionally, Netflix sought to attract more subscribers who resembled these desirable customers. They identified the viewer preferences of these subscribers. Then, they analyzed the movies these subscribers watched. Specifically, they analyzed how often movie scenes with potential actors who were being considered for the new series were viewed and replayed by their target audience.
The net result: House of Cards.
Netflix didn’t set out to develop a blockbuster hit series. According to Fader, they used analytics to create a show that had appeal for a specific, coveted demographic. By doing this successfully, Netflix created greater value for their best subscribers, while increasing loyalty, reducing churn, and garnering more desirable new subscribers.
Can your company react quickly to consumer needs?
Businesses have to look past their typical strategies focused on products and reducing costs, and shift to a consumer-centric strategy. This can pose a challenge for traditionally structured organizations. Historically, brand marketers have addressed specific product lines, at times competing for the same customers within their own organizations. The result was rigid organizational silo structures and a territorial, protective environment where it was difficult to share data or identify emerging trends. The trend now is to foster collaboration and trust between business units, with a focus on innovation, so creativity and solutions can flourish.
Besides recognizing the need to break down their silo structuring, what else are companies doing to navigate and respond to this new era of consumer expectations?
They’re leveraging data lakes, identity measurements, and data ops.
If the term ‘data lake’ is new to you, think of it this way: imagine new data, old data, social data, structured data, unstructured data, and behavior data—all gathered into a giant pool of data, for a purpose or use that is sometimes yet to be determined.
Managing the integration of this data is fast becoming a priority for mainstream companies as they seek to tap into these resources. Companies might leverage the legacy data they already own. They can mine it in new ways, particularly ‘long tail data’, where the numbers or distribution might be trailing off, but collectively, the remaining volume is still able to offer new insights and worthwhile marketing opportunities.
According to MIT Sloan, Management Review, a “significant majority (57%) of firms identified this as their top data priority”, acknowledging that “organizations can now go deeper into their own data before they turn to new sources.”
Integrating structured data, like numbers and variables, with unstructured data, like words and pictures, is another way to harness data and make assessments. The idea is to combine quantitative metrics with qualitative content.
Two examples that highlight the use of data visualization:
A new website, founded by Steve Ballmer (former Microsoft CEO), has launched this week (April 18). The site allows individuals to search massive banks of government spending data, have their inquiry results visualized, and then draw their own analytic conclusions. The development team collected 30 years of federal, state, and local government spending info, then designed a friendly interactive UI experience that allows people to go as broad or deep as they’d like.
This visualization of data collected by Divvvy Bikes in Chicago showed some distinctly different patterns between Divvy’s core user base and non-Divvy members. The data visualization makes it easy to see how non-members were a significant part of Divvy Bike usage on weekends, and seasonally, these non-members tracked significantly higher in summer months. The results help inform future business development plans.
Standards for metrics, KPIs, and customer journey mapping are in flux. There’s a broad consensus about the need to develop measurements and methodologies that provide an accurate and ‘real-time’ representation for both ads and content. The quest is on to develop datasets that deliver valid household data, individual measurements, and out of home (OOH) TV viewing measurements.
According to AdAge: “Even if not all of the multichannel video programming distributors (MVPDs) make their data available to create an optimal nationally representative footprint, vendors are figuring out how to model the data they don’t have, either from panels using meters or automatic content recognition (ACR) technology, or in combination with data from smart TVs.”
The Media Ratings Council (MRC) committee is currently working to develop standards for valid, viewable impressions. And a partnership between the Coalition for Innovative Media Measurement (CIMM) and the Society of Motion Picture and Television Engineers is collaborating to create standardized embedded metadata in digital watermarks. It’s a start, but it still doesn’t fully address fragmented consumer consumption.
The logical outcome for all this data? Data ops. Platforms that provide user-friendly, interpretive interaction with data, AI, and graph algorithms. ‘Interpretive interaction’ is the key phrase here.
Microsoft Azure ML is a leader in this area, with a user-friendly, drag and drop collaborative tool. The ease of integrating this tool with existing Microsoft platforms is a key reason for their success.
The advent of data ops will allow people to integrate into this landscape, asking questions, asking new questions based on responses, while connecting the dots to create a full picture. Decision makers will have an increased ability to see evolving patterns in the marketplace and make informed decisions.
Businesses are looking for data ops to give them the ability to explore, to shape and to mold dynamic data, and provide contextual insights into the opportunities they want to address.
The ultimate objective for businesses
For companies today, the ultimate objective is to deliver relevant, granularly targeted, behavior-inducing moments for their consumers. Reaching the right person at the right time, in the right manner, with the right message, on the right device.
Companies need to figure out ways to determine what consumers want and need and meet those needs in a responsive and effective manner. Businesses also have to be able to act quickly on their marketing insights. This may mean restructuring how they approach marketing initiatives. Some companies are developing small, rapid-response teams within their organizations, groups who can recognize emerging trends and respond accordingly.
The ultimate goal for consumers
Today’s consumers want what they want, when they want, in a manner that serves their needs and interests. The companies who can deliver successfully will be rewarded with loyal brand customers.
Over To You
Is there a brand that you’re impressed with in your personal experience? Has a company or service delivered a great consumer experience for you recently? We’d love to hear about it.
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