30-second summary:
Many marketers are disappointed with the results of their data analytics. According to the Gartner Marketing Data and Analytics Survey 2020, 54% of senior level marketers believe marketing analytics hasn’t had the influence expected.
There has always been a disconnect between what is known about customers and what can actually be known about customers. In recent years, this disconnect has closed significantly. We have an increased ability to merge structured and unstructured data sources, providing more accurate insights.
The key is to make sure that AI technology is delivering the result that you need it to. It can be used to uncover a customer’s purchase patterns, budget and growth projections, and even sentiment signals towards a company and its competitors.
Location intelligence has been part of a marketer’s arsenal for years, but big data offers the potential to gather real, actionable insights about where customers are. Brands can use anonymized data to analyze patterns in the way that people move around cities and build new outlets in locations that will see the maximum footfall.
Data can be used by organizations to create intelligent pricing programs, which react to market activity. This predictive intelligence enables businesses to understand what their customers need before they even do. This can then be used by marketing teams in their conversations with both customers and prospects, leading to a better service and increased revenue.
In today’s world there is more customer data available than ever before. And there are a wide variety of tools that enable marketers to capture a range of data at particular stages in their marketing campaigns. In theory, this should make marketing’s job easier.
However, these factors present challenges. How can this vast amount of data be analyzed to deliver tangible results? And how can marketers make the right technology choices to ensure they remain in control of their tools, rather than being led by them?
At the same time as marketers are dealing with these challenges, customer demands continue to increase.
This poses significant problems for marketers: the amount of data can be overwhelming, while any inaccurate or non-personalized content can destroy a relationship with a customer.
As a result, many marketers are disappointed with the results of their data analytics. According to the Gartner Marketing Data and Analytics Survey 2020, 54% of senior level marketers believe marketing analytics hasn’t had the influence expected.
If marketers really want to make data work for them, they need to be selective with data and ensure they are using the right tools for the job.
Building more meaningful relationships
According to The Global Review of Data-Driven Marketing and Advertising, 53% of marketers claim that there is a high demand for more customer-centric communications. To meet this demand, marketers should start by getting to grips with the data at their disposal.
There has always been a disconnect between what is known about customers and what can actually be known about customers. In recent years, this disconnect has closed significantly. We have an increased ability to merge structured and unstructured data sources, providing more accurate insights.
Now, marketers need to do more to close this gap even further:
It is vital to bring different data sources together to drive better insights
Marketers must look across multiple channels for this data, bringing these insights together no matter where you are serving the customer
Transparency is crucial. Customers want to know which data is being used and how you are using it.
This will lead to deeper personalization that is both meaningful and genuine, creating a stronger relationship with the ever-demanding customer.
Increased relevance with AI
The wealth of data on customer needs is as good as useless if mined on its own. To uncover signals of purchase intent and align to customer needs, marketers need to differentiate between noise and relevant insights.
This is where technology can really help. Artificial intelligence (AI) technology is being rolled out in marketing departments, with Forrester predicting that over 60% of B2B sellers will be enabled by AI and automation in 2021.
The key is to make sure that AI technology is delivering the result that you need it to. It can be used to uncover a customer’s purchase patterns, budget and growth projections, and even sentiment signals towards a company and its competitors.
This insight can be used customize account-based marketing strategies, ensuring that salespeople are having conversations with relevant targets that are actually looking to purchase services.
Looking beyond digital
Of course, data has benefit beyond the digital world. Brands with a brick-and-mortar presence are also able to make use of data intelligence to build relationships with their customers. A great example of data answering a specific question is helping businesses understand where to locate their stores.
Location intelligence has been part of a marketer’s arsenal for years, but big data offers the potential to gather real, actionable insights about where customers are. Brands can use anonymized data to analyze patterns in the way that people move around cities and build new outlets in locations that will see the maximum footfall.
Intelligent pricing
Data can be used by organizations to create intelligent pricing programs, which react to market activity. This means that the cost of services depends on things such as market seasonality and conditions, as well as customer needs and expectations.
This predictive intelligence enables businesses to understand what their customers need before they even do. This can then be used by marketing teams in their conversations with both customers and prospects, leading to a better service and increased revenue.
A data driven future
It’s no secret that data underpins experience that the modern customer demands from brands. But marketers are at risk of becoming overwhelmed by the possibilities, datasets and the latest tools that promise them great results.
True mastery of data in marketing can be realized by assessing what datasets you have available, and ensuring that the data tools that you are selected with an end goal in mind. If data is the new oil, marketers must be able to siphon off exactly what they need and have the tools available to refine it into useful elements.
Iris Meijer is the CMO of Vodafone Business. As CMO she leads a team that shows how Vodafone Business can help consumers succeed. Iris’ passion for marketing and communications came early in her career. She has worked across the world for several leading industry brands. Prior to Vodafone she worked as VP of marketing and comms at Nokia. There she worked globally, spending time on the west coast of the US in particular, where she helped to generate over a billion dollars in revenue.
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