A prospect lands on your website after a personalized email, and comes to a page that explains their exact pain points. The pain points segue into a convincing argument of how the website’s product or solution can solve them and then naturally guides them to the next step with minimal effort and friction.

The promise of personalization is this exact scenario; when you speak to a prospects’ exact needs, they will convert at a higher rate on your offers and engage more with your website content. But many organizations are struggling to realize this promise, despite the Herculean effort involved.

The truth is personalization takes a lot more effort than many marketers ever imagined. When you start thinking about the hundreds of possible permutations and combinations of user journeys, it becomes a daunting task not possible without an army of marketers, content writers and analysts. Many marketers settle for doing the best that you can, mapping out a few, and waiting for the results to come in. But even after implementing the new personalization strategy, marketers are not sure if even those few user journeys are right, and it’s too time-consuming to continually tailor and refine those journeys, let alone expand that level of personalization to every visitor.

There is a better way. Let’s review the most pressing issues faced by marketers implementing personalization and the strategic solutions that other marketers have used.

#1 You’re trying to personalize manually. Without an influx of more people to the marketing department, marketers are settling for personalizing a few user journeys, and ignoring the rest. In doing so, marketers are leaving out visitors that could be very lucrative buyers or key stakeholders to the purchase process that are stopping your deals.It’s like gambling on the right horse to win … and finding out you picked the wrong one.

But what if it is possible to automatically personalize the journey for every single visitor to your website, without hiring 10x more people? What if you could even personalize to the buyers you don’t know about? This is “personalization at scale,” and it’s possible with machine learning.

As we explained in a previous blog post on AI for the enterprise, machine learning automates the analysis and tuning of your search engine to provide the most relevant content for each visitor. If 100 of your visitors all converted on the same offer and shared certain key characteristics, such as their search query, previous pages visited and location, then when the next user comes through with those same characteristics, the website will automatically point them to that offer.

Apply this across all of your website visitors, and you finally start seeing the higher overall conversion rates without mountains of effort or more people.  

#2 You assume that you know customers better than they know themselves. You’ve built personas. You’ve read the market research. You’ve got the support of the sales team. Your personalized messaging is rock solid. What could go wrong?

What if you’re going off poor market research? Or your prospects’ tastes have shifted? Then your personalization strategy – and all of that work – was for naught. The shift could be very obvious, such as new search terms showing up in your Google Search Console for how they land on your site, or more subtle, such as the time of day or previous pages visited that are influencing the content that they need to see. If you ignore any piece of information, you miss the opportunity to provide personalized and relevant content, and an opportunity for a conversion.

Think of the side-show “clairvoyants” who tell you exactly what you want to hear and amaze you by getting it right. The truth is they are using contextual clues you give them, and then tailoring the story (based on their experiences) to what will wow and delight you. Your website can do that too, but many marketers skip the step of leveraging every piece of insight and clue your visitors give to tailor content and provide the best possible chance of conversion.

Get started on solving this issue with our checklist. Download the Roadmap to Mastering the Micro-Moments in Your Customer Journeys Checklist.

 

#3 You’re not refining your personalized messaging to stay relevant.

You can’t “set and forget” your personalized messaging. You need to continuously evaluate if your personalized messaging is still relevant, and automatically refine if possible. Once you start learning from every interaction with every visitor, you will have much greater success implementing the ideal user journey for each visitor.

What you need:

  • Powerful search usage analytics to analyze where you have content gaps. Your visitor logs onto a personalized web page, but doesn’t see the question answered. Their next move is to use your search box – and this is where you see the insight into the queries that return results with low clickthrough rate, no results, and so much more. Use these insights to build a more customer-centric content strategy.
  • Machine learning to automatically refine when possible. Your team should not have to go in and manually adjust the ranking of results. It’s time-consuming with a small visitor base – and it’s definitely impossible with a large amount of visitors. The key is to make this automatic by deploying machine learning to continuously learn from your visitors and refine your user journeys.

Watch our recent Sitecore Virtual Summit webinar, Creating a Data-Driven Content Strategy with Search Usage Analytics to learn more about how your search usage analytics can help you fill in your data gaps for your content strategy.

Don’t give up on personalized marketing just yet. Fixing these three common issues with personalized marketing will get your marketing started on seeing an increase in your conversion rate this quarter.

What are your challenges with personalized marketing? Tweet them to us @Coveo!

About Rachel Schultz

Rachel Schultz is the Content Marketing Manager at Coveo. She blends her background in journalism seamlessly with her B2B marketing expertise and obsession with data to create compelling content for the Coveo community. When she’s not working, you’ll find her reading (strictly non-fiction), hanging out with her puppy or taking in all NYC has to offer with her husband.

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