Here at OneSpot, we believe that the only way to truly personalize the customer experience in a way that aligns with specific consumer expectations is by personalizing to a segment of one. But not just that; the experience must also be refreshed in real time based on the individual customer’s behaviors and preferences. This level of automated, AI-based personalization is what we’ve defined as “individualization.”
When executed with the right technology and measurement capabilities, individualization can lead to some serious (and sometimes unexpected) benefits. Driving deeper engagement across channels, identifying operational efficiencies across the digital organization, and identifying your most valuable audience members are just some of the gains marketers experience from individualizing content experiences.
Here we provide a deeper look at the benefits of individualization and how you can measure them for your business.
Identifying Active Content Users
Who actually reads your content? And who actually reads it intentionally and on a regular basis? General content consumption is one core metric (or set of metrics) that can help you determine if you’re getting eyeballs on your content. But most organizations aren’t looking at how much content a single individual is consuming.
Our data shows that your most engaged audience is consuming 3+ pieces of content in a single session. We call these your “Active Content Users,” and they are the ones who will ultimately be most valuable for your brand. For example, when we compare users who’ve engaged with at least three pieces of content to those who’ve engaged with zero, one or even two pieces of content, we see that Active Content Users have greater brand awareness and brand trust. For one customer, those who saw three pieces of branded content were 41% more likely to trust the brand than those that only saw one piece of content. We also see greater purchase intent and net promoter score: Active Content Users are 45% more likely to recommend the brand and 13% more likely to purchase one or more product from the brand.
Active Content Users are also more likely (20% more likely on average, in fact) to take high-value actions on brands’ websites, including “buy now,” “sign up for newsletter,” and “open account.”
By individualizing the content experience based on a user’s needs and behaviors, your brand is simply delivering the most valuable and relevant content. In exchange, Active Content Users will be more favorable of your brand and reward you for delivering individualized content experiences.
Driving Deeper Engagement
Your typical engagement metrics, like views and visitors, can tell you whether you’re driving traffic to your content, but they don’t tell you if your content is actually resonating with readers who see it. When you’re delivering truly individualized content experiences, you have the ability to measure and track deep engagement. Here are four engagement metrics that enable true insights about your most engaged audience:
- Engaged Pageviews: This is the number of viewers that scrolled down the page at least 25% and remained active on the page for at least 30 seconds.
- Engaged Time: This is the amount of time a user is actively looking at the page as indicated by scrolling, mouse movements, and clicks.
- Click-to-Open Rate: This metric compares the number of people that opened the email to the number that actually clicked.
- Active Content Users: This is the key metric that identifies your most engaged visitors who are consuming at least three different pieces of content in a single session
These metrics help you measure “real” engagement with your content, not just at the surface level. When you’re delivering individualized content experiences that directly impact these metrics, you pave the way for identifying and growing your base of Active Content Users.
Individualization technology can also enhance how your marketing team operates in various ways. AI-based individualization can provide a new perspective on your content portfolio by allowing you to track consumer behavior by individual and by content type, topics, keywords and more. This data can inform your content strategy (like topics for your editorial calendar) and your SEO strategy (by identifying keywords for web page optimization).
As for enhancing your operational model, machine learning tools can dramatically reduce the amount of time email marketers spend on manual segmentation tasks. In a recent report, we found that most marketing teams spend more than 36 hours per week on manual email segmentation. 70% of marketers reported that machine learning would eliminate manual processes (like content selection, content development and list building) and allow them to shift those work hours to more strategic initiatives, like program planning and scaling.
For a deeper look at these benefits and more, download our guide: How to Master Individualization to Delight Your Customers.
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