How to Combine Algorithmic Personalization with Editorial Control
April 2, 2019
As a solutions consultant and architect, I talk to marketers on a daily basis. Every marketer says they want personalization. But I have found there are often major blockers to actually implementing personalization for many of them.
Retailers are beholden to their buyers, while publishers must defer to what their editors have earmarked as the major story of the day. Additionally, there is the simple “trust” factor for marketers, with the following stuck in my head on repeat:
- How do I know this is working?
- I am used to doing things a certain way!
- I don’t know how to do it! Is there a recommended course of action?
Even with all the data out there supporting that personalization is how modern brands will engage and retain audiences, sometimes marketers still get cold feet. They don’t want to let an algorithm make decisions for them – even though it can save them a ton of time and effort. Despite the opportunity to use that time and effort to make better, more strategic decisions that only a human can make.
Publishers want to maintain editorial control. If they have a scoop, they want to make sure every single one of their readers sees it when they open their email, launch their app, or come to their web site. They don’t care if that content is related to international news and a particular reader only seems to care about sports. Sometimes a story is important for other reasons.
Retailers have their own concerns. If they get a shipment of the holidays’ hottest product or are running a flash sale, that product or sale needs to be the first thing customers see when they engage with the brand.
We get it, especially as brands are increasingly prioritizing artificial intelligence. And we’ve got you covered across all scenarios.
Making it Work with Recommendation Manager
Sailthru’s Recommendation Manager allows publishers and retailers to strike the perfect balance of manual control and AI with dynamic, personalized email templates and web pages. At the same time, there is still room to choose manually. Marketers, editors, and merchandisers can pin a certain piece of content in a particular position, and it’s set. Then the rest of the email or homepage can be filled by an algorithm.
Setting up Recommendation Manager couldn’t be easier. Once you’re using Marigold Engage by Sailthru, you can just filter to find the content or the product you want to highlight. If you know the URL, that works, too. Then just click on the position (one, two, three, etc.) that the item should occupy. To make sure it doesn’t move, click the big blue pin and hit save. That’s it. That content is now pinned to that position. It will always appear there. You can even set a timer on holding the pinned position.
With Recommendation Manager, you don’t copy and paste anything. Once you set your template up, select the items you want to pin, pin them, and call it a day. The algorithm will do the rest, personalizing the products or content of every email sent. And if you need to pin everything, that’s fine, too. Either way, you just drag and drop. You don’t have to worry about formatting or cell padding. You receive a confirmation so you know the email went out. And that’s it.
A publisher, for example, could take their hottest story, and pin it to the lead position in their newsletter. Every single person who opens their newsletter will see that story in the hero slot. But other stories are chosen based on the behaviors and preferences the reader has exhibited over time. This same tool can be used to make sure readers see sponsored content.
Likewise for retailers. If there’s a dress that really needs to sell, a buyer can make certain that it appears in the lead position of the newsletter or web site, no matter who the shopper is. If the visitor is a guy who usually just buys socks, a retailer can show him that dress anyways, giving the merchandiser confidence they are mass marketing that product, while still layering in personalized recommendations in the remaining positions.
Blending Content and Commerce
Recommendation Manager is equally at home with editorial content and with traditional merchandising. It treats content and products the same way, and works the same way in both contexts. Unlike some retail-oriented products that stumble over tags or content-based recommendations, Recommendation Manager makes it as easy to change a price as it is to change a subhed.
Marigold Engage by Sailthru’s Recommendation Manager doesn’t just let marketers ease into personalization. It allows readers and shoppers to ease into it, too. If someone regularly opens your newsletters, there’s probably something about those newsletters that they like. So you might not want to change everything at once. Recommendation Manager empowers you to control how much the algorithm chooses recommendations, test, and then choose what blend works for your business. It doesn’t have to be all or nothing. It can be little tweaks until you hit on the combination that works best.
That way, you’ve done more than just personalize for your customers. You’ve personalized for your own organization, as well.
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