Firms that integrate data at the core of their email marketing boost their marketing profit margin by 15-20%, according to a McKinsey & Company analysis of more than 250 engagements across five years.

Multiple organizations across the world enjoy delving into Big Data sets in order to uncover customer data, learn from it, and deliver improved value to clients across a variety of businesses and sectors.

So, how can you accomplish it as well? What is the role of big data in shaping the future of email marketing strategy? In this post, you'll discover more about Big Data Analytics, Big Data Technology, Email Marketing, and how these concepts can come together to empower businesses like never before

What is Big Data?

Big data is the wealth of information that a corporation accumulates every day. For example:

  • Email addresses of customers.
  • The amount and variety of advertisements that have been clicked.
  • Visits to web pages (number and manner).

Businesses benefit from big data because it provides insights about customer behavior, purchasing behavior, what's working, and what's not working. These help shape strategy for the long term.

Benefits of Big Data Email Marketing

Email marketing is a great channel to drive high ROI, and when you combine it with big data, the returns increase many folds.

We'll go over five ways big data is shaping email marketing in 2022:

1) Personalization

Instead of sending out similar emails to a full list of subscribers, marketers can create precisely focused – aka personalized – emails depending on their customers' demographics, geography, and past purchasing behavior.

Changing the content or terminology of an email to reflect a certain customer's wants can capture their interest, connect with them, and improve the conversion rate.

For example, an online gym gear business should not offer the very same emails to 20-something people who enjoy intensive workouts as it would to an elderly person who prefers to keep things simple.

Businesses can also send highly personalized emails that match each buyer's interests by discovering more about each customer's browsing habits, such as the brands and types of gym wear they looked at. This information allows them to create highly tailored email templates that align with each buyer's interests.

Here's an example of using data to personalize emails for an audience:

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Image from Campaign Monitor

2. High-Performance Campaigns

Big data expands your possibilities for segmenting customers based on demographics, purchasing histories, location, and preferred channels to develop targeted campaigns that deliver.

Because you'll be able to understand more about your most valuable customers thanks to big data insights, you'll be able to tailor ads just for them. This allows you to design exclusive discounts that the company might not be able to provide otherwise.

3. Predictive Analysis

Collecting big data helps companies to understand the current purchasing patterns of their customers.

Businesses receive knowledge into the current buying habits of customers, which may then be utilized to anticipate future purchases.

Big data, for example, might reveal which products are usually bought together and the kind of people that make these transactions. When a new client purchases one of the items and fits a specific profile (demographic, sex, overall spending amount, etc. ), a company can improve post-purchase income by sending the new customer a highly personalized email highlighting similar items to their initial purchase.

The approach of proactively reaching out to customers can make them feel special & help you build trust in the digital world.

Predictive analysis helps businesses to gain better insights into what their customers are searching for, what they want, and what products they are buying.

4. Optimizing Subject Lines to Grab Attention

The significance of email subject lines is often overlooked. In fact, it's critical to choose the correct subject line for an email for it to stand out in readers' inboxes.

Marketing experts can use data analysis to test the effectiveness of particular phrases and special keywords to see which ideas work.

Using your organization's big data also allows you to add the recipient's name in the subject field, as well as information about a previous order or contact with your firm. Marketers can also determine what makes their customers open their newsletters at the highest percentage with the use of split testing.

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Image from The Business Journals

5. Providing Feedback

Finally, big data may provide evaluation and an assessment of which campaigns or techniques have succeeded well for your company and which have not. When you combine information about customers' needs and experience with the performance of certain initiatives, you can more precisely target your big data email marketing budget to receive the best return on investment.

Keep in mind, big data can help you tailor campaigns, and achieve success, but it's not going to be cheap or easy. That's why you have to continuously improve your products so that you can reach a point where word of mouth marketing takes over. Then, you will be able to collect even more data and create precise campaigns.

Analytics Models of Big Data That Help Improve Email ROI

As mentioned earlier, big data email marketing allows you to precisely target your email marketing budget to receive the desired and best ROI. Let’s explore some of these analytics models that can help generate improved ROI for companies:

1. Clustering

Clustering is the process of grouping a population of customers or a set of data points into many groups so that data points in the same group are more similar than data points in other groups.

Once you've divided your customers into "like" behavioral categories, you can dig deeper into the data to see how excellent of a customer/prospect they are based on a variety of signals.

2. Propensity Models

Propensity modeling is a set of techniques for creating predictive models that analyze a target audience's previous behavior to anticipate future behavior. Propensity models, in other words, assist in determining the probability of someone executing a specific behavior.

However, action certainty is a forecast, and you must assess the degree of confidence. This might be used to examine your subscribers' propensity to engage, unsubscribe, buy in a particular product or service segment, churn, and so on.

3. Recommendation or Collaborative Filtering

The ability to comprehend a person's taste and automatically identify fresh, appealing information for them based on a pattern connecting their likes and ratings of other products is provided by a recommendation system.

Recommendation engines can leverage other users' likes and desires to compute a similarity metric between users and then propose goods to them based on that. To effectively propose complex products like movies or music tracks, this sort of screening relies on individual opinion rather than machine analysis.

Step-by-Step Approach to Big Data & Email Marketing

Starting a big data project might be intimidating, so here are a few simple steps to get you started:

1. Define Objectives & Problems

It's easy to get wrapped up in the details of budgeting, technology selection, and assembling a project team when embarking on a new project. But don't jump right into these tasks; instead, define the goals and what has to be accomplished first. Consider what issues need to be addressed, when and where information is needed, how frequently it should be updated, distributed, and shared, and what the business impact will be. In any case, you should also work on security measures, implement DMARC policy, check DKIM, and take other steps.

With remote work becoming the new normal of the whole world, it sounds like a behemoth task to take up big data projects, but with a good workplace alignment strategy, things can be smooth as if you are working in a real office.

2. Preparing the Components by Breaking it Down

Even in the case of a real big data scenario, all relevant data does not have to be integrated in order for the evaluation to take place. Examine the most valuable data streams, such as clicking streams, social media, and purchases, and build separate social media auditing, web monitoring, interfaces, and advanced analytics appropriate for each data type.

Choose whether the solutions will be hosted in the cloud or locally. Determine what data is required to solve the issue, and then determine if you already have it or need to obtain it. Determine whether your team has the necessary knowledge to solve the challenge or whether you require extra resources.

3. Executing

Once the goals have been determined, plans have been made, and agreements have been reached, the focus of execution must be on the information that can be quickly transformed into actionable insights and implemented.

Find the most widely accessible sources of transaction and engagement data and establish the path of least resistance to making the biggest effect. Create milestones for the big data journey and, more importantly, allocate responsibilities to avoid trying to do everything at once and becoming paralyzed by the project's scope.

It is advisable to test your big data strategy first. The milestones that can help you in shaping and testing your big data email marketing are:

  • Select the smaller units of datasets that you want to examine. To help the procedure go faster, choose data that you already have.
  • Create multiple scenarios demographic segmentation, purchase history, brand engagement, or competitor data.
  • Set some campaign objectives and figure out how you'll measure them. Use easy-to-measure success criteria to solve the problem.
  • Run the campaign, then assess the results. Look for patterns in particular. Repeat the project on a greater scale if it goes well.

Dos & Don'ts of Using Big Data With Email Marketing

Dos of Big Data Email MarketingDon'ts of Big Data Email Marketing
Make sure your email content looks good on all devices.With the majority of the population checking emails on mobile devices, do remember that you have less space to work with. That’s why you need to make it compact, attractive, and informative.Don’t add filler content or give tons of information about the product. It can be done in later stages. The first step of big data technology is to optimize the email based on the previous customer's information.
Consider your email subject line carefully. This is the first thing your contacts see when they receive your email, and it's crucial for them to open it.Based on previous interactions with other emails, AI copywriting tools can help you predict how clients will react to specific subject lines.Don't forget about GDPR and data security standards.Ascertain that you have the necessary permission to send emails to your contacts, as well as the ability to opt out and alter their preferences.
Do everything you can to make your job easy. Make use of an email marketing automation service.You can create the emails ahead of time by scheduling them to be sent. You can also use an email strategy to guide contacts through a conversion-oriented journey.Do not Spam. It's tempting to use every bit of data available to bombard people with what you think they may like, but it can come across as too obtrusive or overwhelming.

 

Wrapping Up

Big data is here to help the email marketing industry, with improved personalization, useful insights to create a strategy, and ease in supplying real-time data that can strengthen email marketing tactics to increase revenue.

You'll be able to accelerate new email marketing strategies by using these lessons, allowing data to provide you with the information you need to push your potential to new heights.

About the guest contributor:

Trevor is a managing partner of SendX, a powerful email marketing software for sending campaigns, building your list, and automating your marketing. SendX is a product of SendWorks, a software product suite with tools that help send emails that hit the inbox.