January 22, 2018, posted by shahzeb arif
Putting Your Customer Data to Work
In the modern age of marketing, customer data has become a key definer of consumer behavior and needs. Rapid advances in technology over the past two decades have given marketers access to massive amounts of data. Whether it’s shopping for clothes on Amazon or writing a restaurant review on Yelp, everything we do online is being tracked. Marketing departments across the world are seeking out best practices towards manipulating and using this information to accurately predict consumer behaviors and increase profit margins. Those that have been successful are able to enhance customer experiences and recognize and act upon our lifestyle needs.
Collecting Customer Data
You may be thinking – “Collecting customer data? That’s easy! Just gather all the data and put it into a database on Excel, SQL, etc.” Yes, that’s great and all, but it’s going take a lot of manpower to sift through that data and manipulate it properly to predict your consumers’ behavior. What the goal should be when collecting your data is to figure out what data points are most relevant to your campaign objectives.
For example, a campaign from a New Zealand health insurance company, Sovereign, won an International ECHO Award for integrating a wide range of datasets into a campaign with the goal of driving customer signups, lead generation, and sales. Sovereign integrated data streams from activity trackers, gym networks, and grocery stores to reward customers for healthy behavior. By pinpointing which data points were most relevant to its campaign, Sovereign was able to improve health outcomes and increase policy renewals, and as a result, reverse a negative trend for the company.
Personalizing the Customer Experience
We are currently living in the age of data, but more importantly, we are witnessing the age of the customer. Today’s customers demand that businesses meet their expectations for service and experience. So, how can marketers take the customer data they have and successfully meet customer’s expectations? There is no perfect answer, but Kurt Marko, Forbes contributor and independent technology analyst, has a pretty a good idea of what it takes, stating, “Collecting, correlating and analyzing data from customer interactions across channels is the key to transforming the customer experience from nightmare to nirvana. The nexus of big data and machine learning in all its forms, including predictive analytics and even neural network deep learning, are the underpinnings of well informed, highly efficient and deeply satisfying interactions that benefit both customers and business.”
In short, collecting data at every touchpoint is vital for companies looking to create a personalized experience for customers. According to Google Analytics Advocate, Adam Singer, the average consumer consults 10.4 sources (in-store visits, search engines, social media) before making a purchase. As the individual consumer moves through each touchpoint, they help paint a picture of their expectations from the company. It is as if consumers are actually building their own personalized experiences. As a marketer, it is our job to connect the dots and create tailored content for each user.
Companies should act now to incorporate big data and analytics into their everyday processes. Rather than undertaking a massive transformation, executives should build a data strategy that focuses on targeted efforts of collecting customer data, building models, and implementing key findings into campaign strategies. There should be a central structure to an organization’s data capabilities, but it is important to maintain flexibility. The realm of big data is ever-changing, and the information itself as well as the technology responsible for managing and analyzing it will continue to evolve and lead to new opportunities. As more companies implement big data into their overall missions, building superior capabilities will become a dynamic competitive advantage.