5 Keys for Using Big Data Effectively in Marketing
Published: September 18, 2015
Author: Robert Cordray
Big data has a host of benefits for marketers; even SMBs can get in a game once reserved for enterprise-level players. One of the obstacles to big data’s effectiveness is tackling the sheer possibility of employee training and development techniques along with other benefits it provides. Let’s jump into five ways to make significant inroads using big data.
1. Embrace complexity
As leading marketers learn to “let the data do the talking,” they are often surprised by the results. Intuitively, we know that much of a customer’s decision to purchase a particular product or service is beyond our control. This realization that marketing isn’t 100% responsible for a customer’s buying decision (or even 150% in those organizations that double-count sales as an attribution technique) can be a big scare for some marketing organizations. Naturally, a model is only as accurate as the data you give it, so be as comprehensive as possible when thinking about what data to look at. On the content marketing side of things, embracing the growing practice of using increasingly complex data sets and data analysis to tell stories is also important. Examples like the impact of vaccines on infectious disease and the continuing problem of school segregation are good starting points.
2. Trust your data and your model
Armed with a new understanding of your customer, it’s time to look for results. Remember, information can lead to insight, but only action can lead to results. As marketers, we all know that results are what matters. Models that explain the past can give us the information critical to gleaning new insight about our customers. However, models that help us predict future behavior can drive breakthrough results. Leading marketers understand that trusting your data doesn’t mean betting the farm on some new-fangled modeling technique. They combine the recommendation from new predictive models with classical techniques and A/B testing to accelerate the adoption of advanced attribution modeling inside their organizations.
3. Don’t settle for a rear-view mirror approach to modeling customer behavior
Most marketers still use outdated attribution methods to divvy up orders but don’t know how to apply their learnings going forward. The bottom line is that big data and advanced statistical techniques now offer all marketers a level of sophistication that was previously available to only the largest of organizations. With these new tools, marketers can identify the right customers to contact in the channel that each customer is most likely to respond to at the right time for the customer. Accurately measuring marketing effectiveness has important implications for a company. There are various corporate training companies that provides top-notch training programs that educate employees on a large scale on how to implement content marketing plans and models.
4. Handle the paradox of choice
Online businesses (ecommerce portals) offer their customers thousands of items to choose from. Many times this effort to expand their potential market backfires as the customers become confused with too many options. If the companies collect data and correlate it with Customer Intelligence (CI), they can straightaway direct the customers towards customized display. This way the customers will see exactly what they are looking for. For example, Netflix takes all of its customers’ viewing habits and movie ratings and runs them through a sophisticated algorithm to generate the 5-star recommendation system tailored for each subscriber.
5. Offer proactive solutions
With the help of big data analytics, enterprises can predict any issues that consumers could be experiencing with their products or services. This helps the companies be well prepared and provide much faster solutions to their customers. Customers who otherwise could have switched products due to the problem might be inclined to stay since the organization has been proactive. Once the retailers understand the importance of big data analytics, the next challenges to tackle are lack of a proven process, building high-quality data collection, choosing the right big data management tool, and hiring big data analysts to implement it in their business strategy. Don’t wait. Connect with your customers today to win at the loyalty game.