Firefighters contained the San Diego wildfires that raced across communities in California in May after many anxious days – but not before a group of analytics thought leaders and data scientists was evacuated from a conference here almost in mid-sentence. The Anametrix Customer Advisory Board had gathered under the region’s blue skies with a clear focus: raise the bar on how marketing can better engage customers using advanced analytics. But then the wildfires broke out. Disruptions aside, board members – who represented diverse companies and interactive digital agencies – found a great deal of unanimity about the direction that data analytics is taking during the few memorable days we spent together in San Diego.
The market is maturing rapidly. Marketing teams increasingly know what they want from their data. In fact, more and more marketing organizations aspire to do advanced analytics for deeper and more actionable insights. Yet results can be elusive. Accenture survey research in 2013 found that 68 percent of executives were committed to analytics. Two out of three companies surveyed have added senior staff in analytics and the use of predictive analytics is up three-fold since 2009. But only 20 percent of those surveyed reported being happy with the business results of their analytics programs.
Meanwhile, the data technology and services market continues its record of explosive growth, according to IDG analysts. This market is forecast to grow at a compound annual growth rate (CAGR) rate of 27 percent to $32.4 billion through 2017. That’s six times the rate of the IT market overall. Looking just at the advanced analytics market, we see it is forecast to grow from $7 billion in 2014 to $30 billion in 2019, according to Research and Markets. No wonder marketing teams are looking to up their game in analytics.
Advanced Analytics Defined
Let’s start by defining terms. Advanced analytics generates insights into data that go beyond simple visualizations in dashboards and reports. These dashboard tools often lack in-depth analysis, providing only a “temperature” reading of what’s already occurred. In contrast, advanced analytics establishes a foundation for 1:1 marketing, supports highly targeted customer acquisition and retention efforts, not to mention enabling marketers to optimize specific programs based on predictive models. Advanced analytics goes beyond dashboards to interactive reports, leveraging dynamic statistical models. Marketing-specific solutions deliver capabilities like attribution and correlation discovery to explore hidden relationships among seemingly disparate channels, and generate more information about why, when, and where consumers interact with brands across all marketing channels and platforms. The “what-if” analysis enables marketer to explore likely outcomes depending on which actions marketing teams take. The objective is turning data into action, and ensuring those actions are the right ones given the changing constraints.
What Creates Hurdles for Marketing?
Nonetheless, marketers struggle to understand the effectiveness of their campaigns, promotions, content, social media programs, and other forms of consumer awareness initiatives. They must track performance across countless combinations of online and offline channels, mobile devices, and social networks – and find it’s still far from easy. Here’s why:
- Marketing is the last enterprise organization to adopt strategies and tactics requiring “quant” skills. Marketers historically have come to the table with creative talent, not analytical skills. In contrast, other enterprise functions such as sales and finance have been largely driven by metrics. The rise of the data scientist and analytics in marketing reflects the growing need for staffing with quantitative skills.
- Marketing data is unique. Unlike other enterprise departments, much of marketing data lies outside the firewall. Think about finance. Data is generated and managed internally. The same is true for sales data. In contrast, marketing data is largely hosted and cloud-based. The information marketing teams require to analyze their effectiveness is scattered across hundreds of data silos, most of which are hosted in cloud-based systems with only cryptic APIs or flat-file extracts to obtain the valuable data they maintain. These APIs are often brittle and poorly documented. To make matters worse, vendors tracking your data often hold it hostage in closed, proprietary systems. Retrieving that data and using the analytical tools of your choice can be daunting, to say the least.
Connecting the Data Silos
It’s my view that the use of advanced analytics in marketing has been fundamentally stifled by challenges related to data silos. To adopt advanced forms of analytics now in such demand, the marketing team needs to take a first step: get all the marketing data scattered across data silos into one location. Simply put, you first need your data unified to run meaningful analyses across the entire multichannel landscape. This is fundamental. Once the multichannel data is unified, transformed, and cleansed, now you are ready to apply the advanced analytics required to extract real value from these dynamic data sets – to support significant business decisions. And that’s when the real fun starts!
Marketers create personas to better understand their target audience and what it looks like. If marketers can understand potential buyer behaviors, and where they spend their time online, then content can be targeted more effectively.
What’s behind a successful data-driven marketing strategy?
One of the major challenges in the martech industry is getting the attention of prospects in a world where they are bombarded by content and emails on all sides.
Facebook is addressing one of the biggest missing pieces of its chatbot offering: analytics.