Marketers are well aware of the many benefits to be found in the personalization of digital experiences, but consumers don’t necessarily share the same enthusiasm for personalization.
A report from Adobe finds that consumers are split on whether personalized recommendations are:
- well suited (52%) or
- poorly suited (49%) to them,
but are open to better personalization.
Research has shown that the right product recommendations can be extremely powerful, so it’s instructive to see which types of recommendations consumers find the most effective.
When respondents were asked to rank recommendation messages on this message,
- “based on your favorite” was the most popular, making it into the top 3 (from a list of 8) for half (52%) of respondents.
- “Recommended for you” was the next-most common top-3 choice (50%),
- followed by “people also bought” (44%) and
- “most popular” (40%).
Generally, this suggests that consumers have a slight preference for messages that are personalized to them over messages based on a products’ popularity.
Granted, there are a few outliers — the fact that “because you watched” was fifth-most common in respondents’ top 3 (35%) is perhaps due to its more niche association with video streaming, but the relatively low placement of “trending now” and “other people liked this” indicates that popularity alone isn’t too compelling. Read the rest at Marketing Charts.
Beyond Social Media Segment Transcript
David Erickson: This is the most effective recommendation engine tactics according to Adobe. I’m gonna put this on my big screen so I can read it properly.
Adobe Survey of 1000 In US & UK
David Erickson: What kind of recommendations– This is consumers are responding to this; it’s based on a survey of thousand adults in the US and in the United Kingdom, 800 in the US and 200 in the UK. What kind of recommendations are most quote-unquote impactful for you which I…
BL Ochman: I hate that word.
David Erickson: …where I take to mean effective.
Most Popular Types Of Recommendation Tactics According To Consumers
David Erickson: Recommendations that are based on my favorites. So this is personalization type of stuff, right? You know what I like and so recommend more of what I like. Recommended for you. You’ve seen that in Amazon–I’m sorry, based on your favorite: 19% said it is…they rank that first. Recommended for you: 16% rate that first.
And this is a ranking first, second and third.
People also bought: so that type of recommendation, 18% rank that first. Most popular: 14% rank that first. Because you watched this, you should watch that: 13% rank that first. People like you like this stuff, so you should also like it: 8% rank that. Trending now: 6%. And other people like this: 5%. So interesting stuff, we’ll put the whole chart in the show notes.
So you can take a look at all of the data. But, you know, personalization recommendations work, if it’s done right.