How to use data for highly effective marketing
The value of your data
Most businesses know that marketing is essential to bring in new customers and revenue. As long as there has been something to sell, there have been ideas on how to market that product or service to people. However, ideas aren’t enough any more. Since the beginning of digital purchasing, data has been collected from customers on how and what they buy, when they buy, and why they buy. At first, this data was only broadly collected and utilized by the largest corporations and government agencies. Today however, customer data is collected at every touch point and is accessible by anyone who knows where to look.
While accessing data is important, what is even more important is being able to use that data for highly effective marketing. Following are three ways that customer data can be used in combination with big marketing ideas to achieve goals in your critical business metrics.
Knowing your customer
Marketing 101 teaches us that you need to know your customer (the who). While that knowledge is fundamental, it’s only useful if you also know when to reach them, and in what context (how to speak to them, and where).
Customer segmentation is a process in which you group your customers, based on data you’ve collected, into groupings based on similar attributes. This data is typically housed in a CRM, CDP, or a data warehouse. Consolidation of this data is essential so that there is one source of truth that branches out to your marketing tech stack.
Customer segmentation can be as much an art as a science. Decisions need to be made about what customer attributes are important to your business in terms of both nurturing current and past customers, and also who you want your customers to be in the future.
Today social listening tools and data enrichment partners can help fill in the gaps to make customer segmentation decisions easier and make targeting your audience more effective. These tools identify groups of consumers based on stated behaviors (public sentiment on social media, etc.) and unstated behaviors (private actions such as purchases or search). Combined, these tools provide sophisticated marketers with a much more intimate understanding of a customer’s needs and lifestyle.
Executing on your customer knowledge
Once you know who your customers are and how they behave, they should be communicated with using a true cross-channel marketing orchestration strategy. This strategy includes digital tools such as email marketing automation platforms, search targeting, and social media touchpoints (ads, posts, etc).
Important questions to ask while optimizing your marketing orchestration strategy are:
Is customer data across the business stored into a central repository as a singular source of truth for measuring outcomes and making decisions on strategy?
Have you ranked your marketing channels based on effectiveness towards achieving specific customer journey metrics?
How are your digital and offline marketing channels lined up in a cohesive approach to reach the customer at the right place at the right time?
What behaviors are used to trigger personalized communications to influence the purchase journey?
Marketing orchestration requires strong data management, coordination of campaigns, and consolidating granular customer activity and campaign performance data. That closed loop allows you to iterate continually on what is working and what is not.
Predicting the future
Once you have customer segmentation and marketing orchestration in place, your customer data should inform a process called predictive modeling. We can use data acquired through our previous processes to predict and forecast the probability of individual customers to take specific actions. These actions include likelihood to purchase a specific product, likelihood to engage with a specific channel, or even likelihood to churn.
Diving even further into the data, predictive modeling can help develop customer lead scoring models and market share forecasts. The value of this knowledge shouldn’t be underestimated. Not all leads are created equal, and marketing budget allocation should be adjusted appropriately based on a lead’s status in the buying cycle. In addition, being able to forecast market share and either adjust spend based on proprietary probability models makes your marketing efforts both more efficient and effective. Over time, as these models are trained on more data, they become even more accurate and add to your competitive advantage.
Analyzing customer data, while complex, is worthwhile and can dramatically improve the outcomes of your strategic marketing initiatives. Petram specializes in analyzing your customer data using the processes mentioned above amongst others – let us know if you have questions about your own data and how it could be utilized to help grow your business.