The rise of predictive analytics has opened doors for marketers to understand consumers better and elevate the manner in which they communicated and forged relationships with their customers/prospects. Gone are the days in which the scope of predictive tools was confined to simply churning or analyzing data; at present, they are able to provide marketers actionable insights regarding the behaviors and interactions of their customers. What this essentially means is that these tools utilize your current data to give you a highly accurate idea of what actions your buyers might take in the future. With this insight, marketers can now use targeted email marketing to increase response rates and conversions.
Now, I’m sure you have a barrage of questions whirling in your head.
“What components of predictive marketing are critical to success?”
“How exactly is predictive marketing transforming email marketing?”
“Which predictive analytics tools should I be adding to my arsenal?”
“How is this landscape going to shape up in the future?”
Well, you are just at the right place, then. Today, our blog attempts to offer an answer to all these questions, giving you a lucid idea of how predictive analytics can level up your email marketing efforts. Curiosity piqued? Read on to find out!
What Is Predictive Marketing And How It Is Changing The Way We Do Email Marketing?
The term ‘predictive marketing’ refers to using customer insights at the right time to create personalized content that drives the right customers down the purchase funnel. The goal of predictive marketers is to maximize the value per customer.
Predictive marketing works by analyzing customer behavior, interests, and preferences to provide them with customized offers throughout their buying journey. It enables marketers to curate the perfect email for every subscriber and send them at the most appropriate time, significantly boosting conversions. This is different from behavioral email marketing that sends emails based on the past behavior of customers. Predictive marketers use rich data sets to understand each customer’s unique needs and preferences to build a personalized experience.
Targeting the right customers at their known stages in the purchase journey produces better results than traditional mass-email marketing campaigns. For instance, using AI to create granular content for specific demographics can help marketers skip broad messaging and, instead, go straight to personalized emails.
Check our comprehensive Email Personalization Guide that you want to bookmark.
This empowers marketers to anticipate and understand key customer behaviors, such as:
- Their evolving purchasing intent
- Possible date and time of future purchases
- Most sought after product categories
- Risk of them churning
- Customer lifetime value
What Do The Numbers Say?
As reported by MarTechAdvisor, a survey of 579 marketing decision-makers has revealed key insights about the impact of predictive marketing in emails.
According to the results:
- 82% of marketers consider email marketing to be a necessity for keeping up with their competitors.
- 78% of the marketers agree that soon, all marketing will become predictive.
- 81% of the marketers are willing to increase their foothold in predictive analytics while driving key marketing decisions.
Exploring the Rise of Predictive Analytics
The popularity of predictive analytics has shot up enormously among marketers over the last few years. By 2027, the prescriptive and predictive analytics market is expected to touch a jaw-dropping figure of $35.45 billion. Now, this widespread and fervent acceptance can be attributed to a number of factors:
- It has become easier for marketers to gain access to high volumes of customer data.
- Predictive analytics tools bring to marketers a host of sophisticated automation tools and computing capabilities which they can utilize to strengthen their operations.
- These tools can be easily integrated into a wide variety of platforms, thereby making it possible for small and mid-sized businesses to level the playing field.
- The return on technology investment when it comes to predictive analytics platforms, is immense.
How Can Predictive Analytics Be Leveraged in Email Marketing?
Predictive marketing can significantly increase the efficacy of your email marketing campaigns, all while helping you conserve all-important time and resources. Listed below are some notable use cases of predictive analytics in email marketing.
1. Making an Indelible First Impression
As your brand’s first line of communication, the importance of a neatly crafted welcome email can’t be overstated. Not only does a welcome email familiarize new prospects with your brand’s tone and offerings, but also sets their expectations for future communications. On average, welcome emails register a click-through rate of 14.34% which is thrice the figure that regular newsletters muster. It goes without saying, thus, that should your welcome email campaigns happen to hit all the right notes, nothing can get in the way of your prospects being converted into customers.
Now, if you want to amplify your returns further, throw predictive analytics into the mix. Utilize the data of how and where they signed up for your brand’s communications to deliver welcome emails that are personalized and extremely impactful. Since predictive marketing can help to segment customers into relevant small groups, it facilitates more effective targeting.
2. Crafting Compelling Subject Lines
Writing personalized subject lines is something that most of us have come to regard more or less as a thumb rule. But with customer behavior constantly evolving, maybe the time has come for us to pause and re-evaluate this. According to GetResponse’s 2023 email marketing benchmarks report, the CTR of non-personalized subject lines is nearly twice of their personalized counterparts. Now, this doesn’t mean, in the slightest, that you should abandon personalization, but it definitely serves as a sign to modify our very definition of personalization.
To date, the majority of email marketers out there continue to rely on “first-name personalization”- inserting the recipient’s first name in the subject line directed at them. And the decline in the performance of personalized subject lines can largely be attributed to this particular tactic losing its charm. Customers these days are extremely sensitive to the ways in which they are being communicated with, and using run-of-the-mill personalization tactics isn’t going to take you far. To truly deliver a personalized experience, you need to dig deep into your recipient’s activities and buyer profiles and address things that are directly relevant to them. And who’s going to help you in this endeavor? Why, predictive analytics, of course!
3. Using Dynamic Content Based On Customer Behavior And Preferences
Using real-time data and AI allows marketers to understand their subscribers and serve them specific content that speaks to their needs and interests – not just what they’ve done in the past. This results in better open rates, higher click-through rates, and more conversions.
By identifying how customers are most likely to respond to emails, as well as what type of content they’re most interested in, you can provide highly targeted email marketing services that will produce better engagement.
Using real-time feedback and AI makes email marketing more dynamic and personal – resulting in a positive impact on your business’s bottom line.
4. Using Recipient Data To Ensure Higher Deliverability Rates For Their Emails
By identifying key factors that impact email deliverability, such as IP address blacklists, marketers can ensure greater success when it comes to email reach.
For instance, marketers can find out which ISPs are more likely to block their emails by using predictive algorithms to sift through the “Spam Complaints” report of any ISP in their list. They can then work towards improving delivery rates for their emails by taking steps to avoid being marked as spam, such as creating a clear unsubscribe option.
5. Personalizing Email Content To Real-Time Intent
With predictive analytics, emails can be customized for every subscriber’s current stage in the buying process. This helps to provide hyper-relevant email offers instead of sending generic messages that may lack context.
Emails can also be customized for specific customer behaviors or click-through rates. For example, marketers can create two different versions of the same email. One version is sent to customers who have opened an email within the last ten days, and another version is sent to those who haven’t opened in 30 days.
6. Identifying Risk Indicators Against Churn
Predictive marketing leverages AI to identify red flags in subscriber behavior that demonstrates the threat of churn. This allows you to act quickly and save your customer relationships before they leave forever!
For example, when an email subscriber hasn’t engaged in a while, marketers can send an email to ask them why they haven’t opened any emails lately. If the subscriber’s response is something like ‘I’m getting too many emails’ or ‘You send me too much promotional stuff’, you know that the account has at least some problems.
However, if the subscriber responds with ‘I’m travelling a lot’ or ‘My work inbox is getting clogged’, then you know that you can take corrective measures to win back their business.
This type of dynamic segmentation allows marketers to be proactive and deliver personalized content – which keeps your customers happy and reduces churn rates.
7. Building Better Omnichannel Experiences
Predictive analytics allows marketers to look at all interactions that a user has with any touchpoint and understand what is relevant when it’s relevant to them. This helps you deliver a personalized experience throughout the entire lifetime of the customer.
In addition, because your customer data is always up-to-date, you can make smarter decisions – such as knowing when it’s the best time to cross-sell or upsell with the right emails.
So, before making any big decisions around marketing campaigns, you can leverage predictions to ensure that you’re making data-driven decisions and setting yourself up for success.
8. Sending Recommendations That Strike a Chord
By churning critical data points such as CTRs, past purchases, and browsing history, predictive analytics tools can help you serve recommendations that align perfectly with your subscribers’ interests and preferences straight into their inboxes. This, of course, has several merits- improving user experience, fostering customer loyalty, strengthening deliverability, and fostering up-selling and cross-selling opportunities to list down a few.
You see, in 2023, customers no longer look forward to maintaining just transactional relationships with brands. They are extremely aware of the data they share with you, and they expect you to act on it to deliver an experience which is both fulfilling and rewarding for them. When you deliver personalized recommendations, you are essentially letting your customers know that you are carefully monitoring their interactions with you, and that you are perpetually committed to ensuring that they get their time and money’s worth from your brand.
9. Rousing Dormant Subscribers Out of Their Slumber
As your business grows and occupies more and more calendar years, you are bound to find a few dormant subscribers in your email list- buyers who, perhaps, used to be quite active initially but over time have found themselves increasingly disenchanted with your brand. Every email marketer worth their salt knows that winning a new customer is quite expensive compared to winning back old ones. And hence, focusing on developing stellar re-engagement campaigns must become your priority. Garden-variety “We miss you/ We haven’t heard from you in a while” campaigns don’t make the cut anymore.
With predictive analytics, you can process historical data to determine for sure the specific set of things that used to grab their eyeballs in the past. Accordingly, you can come up with hyper-personalized reactivation emails that will give you a strong shot at reviving your dormant subscribers. What’s more, you can also leverage these tools to apprise yourselves of the ideal send time for this particular crop of subscribers, thereby further amplifying your campaign’s impact.
10. Effectively Gauging Lead Quality With Predictive Lead Scoring
Lead classification is an extremely important part of conducting business. Different individuals interact with your business with different intentions, and thereby they possess varying likelihoods of conversion. If you don’t score this likelihood right from the outset, you’ll falter at creating targeted campaigns subsequently, eventually hampering your sales figures.
Predictive analytics tools take into account customer’s demographics, interests and preferences, location, and other important factors to identify high-quality and high-value leads, making it easy for you to target them effectively.
Predictive Analytics Platforms You Can Consider Adding to Your Toolkit
To help you make the most of predictive analytics in your email marketing platforms, there exist a bevy of top-notch platforms in the market. From helping you gather critical insights corresponding to each customer touchpoint to allowing you to respond to your customers’ real-time interactions via your communications, these tools help you achieve it all!
Listed below are a few tools which when integrated with your business, are sure to supercharge your marketing efforts.
- Mailchimp
- SmarterHQ
- Boomtrain
- Windsor Circle
- AgilOne
Wrapping It Up
Thanks to predictive models in email marketing, marketers can now sift through copious amounts of customer data to make highly informed customer engagement decisions. Such data-heavy approaches have given marketers today the opportunity to pinpoint customers’ needs at ‘quantumesque’ levels, making the future of email marketing brighter than ever!
Rohan Kar
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