Bridging the Gap between Data Collection and Implementation
FREMONT, CA: The whole mystery surrounding the Big Data seems to be unresolved till date. To deal with the humongous amount of information floating around and to come up with a blueprint of a strategy, seems rather too herculean and challenging a task for the Chief Marketing Officers (CMO) and customer strategy executives. In coming up with a grand solution, most of the executives assume that they should develop a comprehensive big data strategy.
One of the major observations made by experts is that marketers are proficient in data collection, however, when it comes to implementing the technology they lag behind. A study by Direct Marketing Association (DMA) and Winterberry Group, a strategic consulting firm, shows that marketers value the demand for data integration more as compared to the required implementation of technology and training.
Majority of the respondents agree to the fact that aggregating different data sources is considered a top priority at their firms. However, they also say that integrating new technology with existing tools was a challenge for their organization. Further responses indicated that marketers had their work cut out for them in these areas.
The study also found that though marketers took initiatives to focus on technology, it was not enough as the focus still lay on data collection. About sixty percent of the respondents said their firms would prioritize integrating and activating new data sources. 56.7 percent of the respondents felt like evaluating current marketing technologies and see how they were using them, and 53.8 percent said they would focus on checking out new options. 54.8 percent said they would prioritize staff training when it came to getting employees caught up.
DMA and Winterberry also believe that there is a need for the alignment of technological tools and the skill sets needed to implement them.
Based on a study from the Economist Intelligence Unit, providing forecasting and advisory services, Jeff Bertolucii from InformationWeek writes that business executives recognize the importance of data analysis and yet many of them claim that marketers' limited ability to analyze data is a major roadblock to executing better big data strategies. When asked which skills were most necessary for a successful marketer today, 37 percent of executives said that "using data analysis to extract predictive findings from 'big data'" mattered most. Five years ago, according to the report, just 17 percent of executives said this was true.
The survey of over 300 Canadian CMOs conducted by Deloitte Canada and the Institute of Communications Agencies (ICA), reveals that one of the key challenges CMOs face in harnessing analytics is a gap in their own skill set. Fifty-one per cent of CMOs said they “do not have the in-house skills to harness data.”
Eighty-nine per cent of CMOs believe that digitization has changed the role and content of marketing; 80 percent said the expectation of marketing from within organizations has “increased dramatically.”
An eBook by McKinsey Big Data, Analytics, and the Future of Marketing & Sales suggests that companies need to invest in an automated “algorithmic marketing,” an approach that allows for the processing of vast amounts of data through a “self-learning” process to create more relevant interactions with consumers. Predictive statistics, machine learning, and natural language mining are some of the ways. These systems can track key words automatically and make updates every 15 seconds based on changing search terms used, ad costs, or customer behavior. It can make price changes based on customer preference, price comparisons, inventory, and predictive analysis.
McKinsey analysis of more than 250 engagements over five years reveals that companies that put data at the center of the marketing and sales decisions improve their marketing return on investment (MROI) by 15 – 20 percent.
Therefore, there isn’t an immediate solution to the problem faced by the CMOs and the executives, however, certain steps could help them address the present situation. The initial plan could be to revise one’s business objectives and to come up with a data-driven marketing technology to meet them. Then one needs to develop a data and analytics strategy plans.
New ways should be found out to curtail the time being spent on mere data collection. The focus should rather be on how to draw conclusions from the data collected and then implement them. Implementation of the technology should be one of the most important aspects. Implementing technology is not enough though, training employees on how to use technology and proving its value are also important.
The priorities should be set and worked upon accordingly. Data should yield a result that is the whole point of collecting the data in the first place. Data collection and analysis should indeed go hand in hand.