Email continues to be one of the main channels marketers use to deliver content to customers. And while the ROI of email personalization is high, many still experience frustrations with it (especially when it comes to having enough resources). 46% of marketers say email personalization is a top priority, but 35% say that personalization is merely “on the list of priorities” and is, therefore, something that may not come to fruition for some time.
At the same time, a notable percentage (18%) aren’t actively personalizing the customer experience. Instead, they settle for easy-to-implement tactics that seem to check the “personalization” box, but don’t deliver true content personalization—78% of marketers currently leverage basic first name personalization to customize messages.
So, what’s holding email marketers back? Recent studies show there are a variety of culprits—the main ones being lack of resources (62%), siloed data (32%) and lack of know-how or expertise (26%).
As more teams invest in email personalization, technology—especially tools that leverage artificial intelligence (AI) and machine learning—can help remove these obstacles and drastically enhance email personalization efforts through automation. Here are a few examples of how.
Reduce Time and Resources Spent on Manual Processes
Email tools that are based on machine learning allow machines to take over the more operational tasks associated with email marketing. By shifting manpower resources away from tactical work, you can enable your team to focus on more strategic email personalization priorities, from planning and content strategy to analytics and optimization.
For example, we learned that most marketing teams spend more than 36 hours per week on manual email segmentation to deliver personalized content. This includes tasks such as content selection, content development and list building. 70% of those surveyed reported that machine learning would eliminate these manual processes and allow them to shift those work hours to more strategic initiatives, like program planning and scaling.
Offer Scalable Content Analysis
While many email personalization solutions claim to operate through machine learning, they still rely on human resources to categorize content. Technology based on true AI and machine learning are able to deeply understand the substance of a piece of content, not just the keywords associated with it. As a result, these tools are able to automatically identify pieces of content that are relevant to a specific segment or individual. This removes the burden on an email team to manually select content for each segment, making email personalization less resource-intensive and far more scalable.
Provide Truly Individualized Content Experiences
By harnessing automated tools powered by machine learning, email marketers can go beyond picking content for broad segments of recipients and instead use an individual’s past behavior to determine the content that will be most relevant to them. The right tools can analyze your content database and customer data at the most granular level and then deliver individualized experiences (in an automated way) via email and beyond.
Marketers win by saving time and email subscribers win by getting more relevant content delivered to their inbox.
Learn more about OneSpot InBox for more details on how machine learning based email personalization technology can identify and deliver the most optimal pieces of content to each individual email subscriber.
Damian is SVP Customer Success & Business Development at OneSpot.