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Business Intelligence In Marketing Explained

What is business intelligence in marketing and why is it such a significant component for modern campaigns?

For business owners and marketers, it can be difficult to fully understand the connection between technology like business intelligence and more traditional initiatives involved with typical marketing campaigns.

We know this can be difficult simply because the uptake of tech like BI is very low among organizations today.

The global adoption rate of business intelligence—even simple cloud applications—across all organizations is just 26%.

The question for many today is to what extent can business intelligence bring improve their operations and what tangible benefits can be realized through adoption.

That’s what we’re going to be looking at in today’s blog.

What Is Business Intelligence In Marketing?

Business intelligence in marketing is mostly concerned with leveraging customer data to achieve better outcomes in marketing initiatives.

In practical terms, this means using identifying information about customers to better target them in marketing campaigns.

The majority of companies, lacking any kind of business intelligence in their marketing, simply have no idea to whom they are marketing and consequently how to best market to them.

This leads to a scattershot approach with campaigns, where for example emails a sent en masse with little regard for audiences and a lack of personalization—leading to disappointing click-through rates and engagement.

With business intelligence in marketing, organizations can use customer information to build profiles, segment audiences for more efficient campaign targeting, and receive higher quality insights into reporting on campaigns.

What Does Business Intelligence In Marketing Comprise?

Let’s get into the nitty-gritty of what business intelligence in marketing looks like in practice for a company by taking a look at the individual elements that make up what BI is.

Better Reporting

First and foremost, businesses for the most part wanting to implement a form business intelligence in their marketing will have to integrate the tool with their existing customer relationship management (CRM) platform.

For example, if you’re using Dynamics 365 CRM, typically it will be paired with PowerBI, thought there are numerous solutions available on the market.

Once this is in place, users can add business intelligence dashboards into their CRM for tracking, analysis, and reporting.

Most CRMs like Dynamics 365 CRM will already have a built-in dashboard for reporting, but it doesn’t come close to the capabilities and depth of an integrated BI platform.

Integrating the advanced analytics of PowerBI into the Dynamics CRM is as simple as entering a URL, enabling PowerBI visualization, and adding the fields you want to report on.

PowerBI (as with other business intelligence suites) allows you to connect data from over 120 supported sources—meaning data housed in practically any application can be imported and reported on in your CRM with BI.

Once you’ve embedded BI (and your data) into your CRM, reporting on your data through a unified platform is significantly easier and more user-friendly than before.

Predictive and Prescriptive Analysis 

Predictive analytics refers to using data to assess trends and uncover likely outcomes in the future weeks, months, and even years.

By integrating data into a business intelligence tool, the platform can use machine learning to determine what is likely to happen and thus inform what approaches a business may want to employ to make the best of their campaigns.

It does this by assessing past trends and recognizing how these will come into play in future—this is particularly useful when a business is anticipating fluctuations in sales and service due to seasonal considerations.

Consider, for example, buyer behavior. Understanding the behavior of customers—what they’re interested in; why they’re not completing orders; why they buy products at certain times of year; why they do not respond to particular email campaigns—is crucial to be able to market to them effectively.

  • Predictive intelligence shows a 40.38% increase in revenue after 36 months of implementation.
  • 34% of purchases are influenced by predictive intelligence recommendations.
  • Website sessions that are influenced by predictive intelligence achieve a 22.66% increase in conversion rates.
  • (Source)

All of these aspects of a customer’s or prospect’s behavior can be determined by assessing the data with business intelligence and giving yourself actionable information that can better position you for marketing to them in future initiatives.

A typical example of using predictive analysis for the purposes of marketing is using purchasing behavior to help shape how you approach existing customers.

If a customer or group of customers has a history of buying a particular product, that information can be used to then inform a targeted email campaign recommending similar products for them. Many e-commerce sites use this technique very effectively, and you likely have such emails in your inbox right now.

This kind of highly targeted marketing is only possible through business intelligence in marketing and adds a level of personalization that modern consumers value very highly.

Related Post: How CX Demands Are Driving New Tech Changes

Segmentation

Segmentation concerns the division of your audience into groups depending on several different factors:

  • Demographic segmentation: Sorts customers based on age, income, gender, race, occupation.
  • Geographic segmentation: Sorts customers based on region and where they live.
  • Psychographic segmentation: Sorts customers based on interests, opinions, values, lifestyle.
  • Behavioral segmentation: Sorts customers based on patterns in their decision-making, such as purchases, use, consumption, and product preferences. 

This information can be used to help group together audiences based on common interests, locales, beliefs, and behaviors and give businesses the opportunity to target them in a more granular and personalized way.

Through the advanced data analytics of business intelligence in marketing, these outcomes can be enormously beneficial to organizations looking to better serve their customers and prospects.

  • 86% of companies with high ROI reported that personalization made up 21% or more of their marketing budget.
  • Businesses with a full or partial personalization strategy experienced revenue growth 78% of the time.
  • 93% of businesses with an advanced personalization strategy experienced revenue growth

Bottom Line

Business intelligence in marketing may seem complex, but really it’s about using existing customer data to better inform marketing initiatives by giving companies improved insights into their customers and prospects.

Through better reporting and unifying data and applications, organizations are able to use their information in a more actionable way to execute more effective marketing campaigns.

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