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How to Incorporate Data Science Into Your Marketing Stack

Utilizing data science is a critical piece of a successful marketing campaign. Compared to data analytics, an equally important tool in marketing strategy, data science attempts to assess customers’ future needs and behaviors. It may surprise you that the data you collect sometimes conflicts with your intuitions about your own customers. For that reason, and many others, focusing primarily on data can transform the way you think about marketing. 

Depending on your industry, product or service, goals, and budget, you can integrate data science marketing into your business strategy to keep up with your customers’ needs and wants. Here are a few reasons to get started: 

Why Data Science in Marketing is Important

The benefits of data science are somewhat clear-cut when it’s broken down. Unlike data analytics, which pulls various metrics from existing data to better understand consumers’ current base, data science is intended to predict future behaviors. Once you’ve adopted an effective data science strategy, it can help your business in the following ways:

Finding the Optimal Audience

You want to make sure you’re targeting the right audience so you can get the best value for your marketing dollars. Data science can help you determine who fits in that target market and whether or not that audience is expected to change. Data scientists often pull from cultural and trend analysis to determine how the market will change in the future. The same strategies can be used for lead generation for sales companies. 

Smart Insights

Data science can help businesses target which marketing endeavors are the most effective, and it’s the job of a data scientist to find causal relationships that an analyst might not otherwise have noticed. 

Data scientists use something called Smart Insights, a machine learning feature, to pick up on minute data that points to hidden patterns and complex relationships. Once they’ve identified such relationships, they can pass that information to growth marketers, who are equipped to reverse engineer it into an effective marketing campaign. 

The use of Smart Insights can help marketers be more unique and therefore more effective with their campaigns.

Increase Customer Experience and Customer Retention

Curating an excellent customer experience may directly impact your profits. Data scientists can identify the features of your business that are drawing in customers and those that might be pushing people away. 

Using that information, you can make improvements to your online store or business, knowing those changes are backed by data. Something as small as a 5% increase in customer retention correlates with a 25% increase in profits, so an investment into data science could be a game-changer for those struggling with one-time customers. 

High-Performance Omnichannel Campaigns

Omnichannel marketing is expected to become the new standard in digital marketing. Using user data profiles and pretty intuitive data science, omnichannel marketing takes a customer-centric approach to create a unified brand message across digital channels. 

For an online store, that could mean sending promotional emails or texts while a customer is looking at a product; it could also be an ad on an individual’s Facebook page for that same product. The idea is to keep that product on your customer’s mind until they finally press the “Complete Purchase” button, and it’s only possible through the use of data science. 

The list of benefits goes on, but we’ll move on to the “how-to’s.”

Screenshot of Google Analytics

First, Track your Website and your Customers

Now that you understand some of the inherent benefits of data science marketing, let’s talk about how it’s done. Start by using a website analytics tool and a marketing analytics tool. The website analytics tool provides insight into your website’s performance and can tell you how customers engage with your website. 

A marketing analytics tool will provide a more holistic view of your customers and tell you what the customer journey looks like. For example, how much time is each customer spending on your site? What type of products are they looking at? Having the ability to track a potential customer’s use of your site can be a precious tool and tells you what is working and what isn’t. 

Google Analytics

Google Analytics is a popular website analytics tool that tracks your website’s performance. It pulls important metrics which can help you develop an informed marketing strategy. A few of these key metrics are website traffic, bounce rates, new visits, time spent on a site, and other user behavior variables. 

Google Search Console

Search console can help you monitor your site’s presence on Google Search results. If you’re experiencing issues with search rankings and spam, you can troubleshoot those problems and set up alerts to be notified when they happen. Google Search Console also shows you which sites are linking to yours. 

Bing Search Console

The Bing Search Console can keep you up-to-date with your rankings on Bing Search. Maintain your site’s presence on Bing Search results and troubleshoot issues with indexing or spam.

Audience Analytics

Social media advertising tools like Facebook Ads and LinkedIn Ads can bridge the gaps between all marketing channels. They collect people-centric and closed-loop data on the following metrics:

  • Traffic-based metrics like CTR, Quality Score, Clicks, and more
  • Conversion-based metrics like cost per action
  • ROI-based metrics 

According to Facebook, an average user clicks on about 12 ads per month, giving it huge potential as an advertising platform. But maybe Facebook isn’t the place to reach your target audience and you’re better suited to Twitter or Instagram. 

If you decide to run an ad campaign on social media, be sure to utilize the insights available to business users. Facebook, Instagram, LinkedIn, and Twitter all provide useful audience analytics on their Insights pages. Learn about when your target audience is online, where they’re located, what their online activity looks like, and much more.

If you decide to use paid ads for your product or service, be sure that you’re using them effectively and avoiding mistakes. A successful ad is a smart ad. 

Web Analytics and Marketing Analytics Together

Used in unison, both analytics types provide a more thorough understanding of a customer and their journey on your site. Use this data to do more informed marketing and answer deeper questions. 

Transactional Data

Transactional data can tell you a lot about your business. Compared to user data, transactional data tracks purchases, returns, payments, signups and subscriptions. Internally, it includes other parts of your business like payrolls, invoices, contracts, and anything else having to do with an exchange or agreement. 

If you run an online store, transactional data should be at the forefront of your marketing analysis. You can dig into the who, what, when, where, and “how much” for each purchase to try and perfect your customer experience. Are customers buying more when you offer bulk discounts? Are you losing money on returns? Ask yourself these questions and develop marketing campaigns around customer purchase patterns.

Image of predictive analytics

Utilize Predictive Analytics

Now that you have a better understanding of your site and customers, you can use that data to create a model to predict future outcomes by utilizing predictive analytics. 

What is Predictive Analytics?

Predictive analytics use data to make predictions around unknown future events. Doing effective predictive analysis involves data mining, statistical analysis, and machine learning methods to find and analyze patterns in data to identify the likelihood of future outcomes. 

After collecting data, consolidating it, cleaning it, and combining it with other marketing data, it’s used to build a predictive model. Here are the 5 most common predictive analytics models:

  1. Classification answers yes or no questions based on historical data. 
    1. “Is this customer going to cancel their subscription?”
  2. Clustering groups your target market into clusters based on shared attributes, then develops subtypes of marketing strategies for each.
  3. Forecast uses historical data to make numeric value predictions on future data.
  4. Outliers model identifies data anomalies that may be relevant. 
  5. The Time Series model looks at historical data trends over time and tries to predict future iterations of that data.

Now imagine how beneficial the use of one of these predictive models can be to your marketing strategy. Predictive marketing can help inform future marketing decisions by determining the likelihood of certain events in your business. 

You can use a predictive analytics tool online, such as ones available from IBM, SAP, and Oracle. These are relatively complex and expensive, and there are quality alternatives such as Tableau, Domo, and Marketo. 

Data Science and Marketing

Data science marketing is more popular than ever before because it offers a much higher ROI than other marketing analysis forms. It is a valuable tool that should be utilized in your marketing strategy because it can help you understand your customers more. The more information you have on them, the more informed your marketing decisions will be, and the more successful you can be in business. 

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