While Many Marketers Are Exhausted By Big Data, A Focused Program Will Ensure Real Results
Big data dominated marketing-related headlines a few years ago, hitting its peak around the time the term was included in Gartner’s Hype Cycle for Emerging Technologies in 2013. Many marketers bought into the hype, believing the promise that big data would lead to deeper customer insights, more granular targeting and better campaigns.
But, marketers now realize that it’s called big data for a reason. With its daunting magnitude and complexity, most didn’t know where to start, and many who did struggled mightily. In fact, the “Marketing Flab to Fab” study released by Resulticks finds that 34 percent of marketers are exhausted by big data, and one in five have given up on big data completely. Further, a third of marketers believe that big data is overhyped, meaning the concept is more fantasy than reality.
For the best results with big data, marketers need to plan and train methodically just as they would with a fitness program. Here are four tips that can strengthen your big data strategy with realistic goals, the right approach and incremental increases in scope.
Phase your approach to big data
Marketers should take a phased approach to data consolidation and laying the foundation for an effective strategy. Start with clearly defining your business objective. Are you hoping to improve engagement rates? Sales for a new product? Average order value across all customers? The more specific the goal, the easier it is to determine the right data needed to work towards it.
Then, identify the first- and third-party structured and unstructured data you need to meet your goals, and determine the required volume of data and frequency of capture.
Finally, assess the best existing sources of data within your organization, the new data needed to fill any gaps, and map out the data collection points. With this, you can increase the complexity – and, subsequently, results – of your big data strategy.
Consider this example. A young professional is chatting with friends on Facebook about his plans to purchase his first condo. A mortgage lending company with conversation monitoring capability would pick that up and post an ad pointing the user to their easy, low-interest loans for first-time home buyers.
Push through data fatigue
There will be times when you question whether it’s worth the effort to continue investing time and resources into big data. Results don’t appear immediately, which can lead to burnout. In fact, SMBs should expect a a minimum of six months to big data working enterprises can reasonably expect 12 or more.
This time investment is warranted given all that a marketer must consider and enable during this period. To get to the next level of data-driven marketing performance, marketers should:
- Identify disparate data that must be consolidated, such as stand-alone databases and Excel spreadsheets, and import all the data into a central hub as a one-time or ongoing activity.
- Once the data has been consolidated, budget for data clean-up efforts to eliminate duplicate, redundant or erroneous data across the organization.
- With any data integrity problems resolved, isolate the data and attributes that can best meet your business goals and drive measurable results.
The data-consolidation phase can be painful, but it’s a required step before moving into technology implementation.
Find the right technology tools
Successful campaigns require technology tools designed to help businesses make the most of their data. Before making an investment, however, determine how well your current infrastructure can handle real-time data inflow, in terms of processing and reporting. From there, consider which option is best for your business’s unique needs. This could include an evaluation of big data platforms, SQL vs. NoSQL databases, analytical tools and integration solutions.
Track results and identify ways to improve
After a few months, take a step back to analyze the results of your data-driven marketing campaigns. Like with a strength-training plan, you may have to adjust your strategy to maximize results.
This is the time to identify new data collection points, augment existing profiles with progressive profiling and determine what data you still need to drive the best results. It’s hard to predict this upfront, which means testing and iteration are often necessary.
Over the past decade, marketers have grown weary of big data, while some have given up altogether. But if done right, big data can lead to new business insights that can be shared across the organization. Combining owned and earned data, like product ownership and social conversations can open up completely new and exciting opportunities for sales and data monetization. With the right regimen in place, marketers will finally be able to lift the weight of big data.