Every day, more and more businesses are realizing the potential of Instagram as a platform for advertising. While this social network may seem like a young upstart compared to Facebook or Twitter, with limited targeting capabilities. It is undoubtedly making strides in its ad performance particularly with video ads.
But what’s often overlooked when reviewing Instagram reports is the data surrounding suggested Instagram for you. To help you do just that, we’ve put together two hacks:
Hack #1: Take advantage of suggested friends and suggested users to build your target audience
This hack is all about improving suggested friend performance. As we mentioned earlier, suggested friends are a suggested feature – it’s up to you to use the suggested follower lists Instagram provides as your suggested friend’s list.
Don’t waste suggested friends Like suggested posts, suggested friends are a suggested feature you can take advantage of to improve your Instagram ad performance – but only if you use it as suggested. For example, last year we implemented suggested friends for an e-commerce client based in Australia.
On average, the brand was seeing 15% lower Instagram suggested for you scores than suggested posts. In other words, ads with suggested friends performed worse compared to those without suggested friends – probably.
Because suggested friend lists were automatically being populated from the accounts of users that had been shopped on their site. Or bought from them before, rather than reflecting their brand or business interests and industry.
Making suggested friends work for you suggested friends lists include both suggested users and suggested friend. Allowing you to build your suggested friends list based on either your current followers or the people they are connected with.
To understand which suggested friend list was providing better results for this e-commerce client. We split-tested suggested user versus suggested friend performance. After examining the data, the suggested user was the clear winner.
To be specific, suggested Instagram for you’ lists were generating 20% lower suggested friend scores compared to suggested users. Despite suggesting accounts similar to their existing followers who had bought from them before.
We couldn’t prove why this was happening, but we think it’s because suggested users included accounts that hadn’t shopped with them before, so suggested friends were actually adding to the number of relevant accounts they were following. As a result, suggested users delivered more relevant suggested friends’ data.
The results suggested user lists saw suggested friend scores 28% higher than suggested friends. List in this particular ad set – not only did this increase suggested friend engagement rates by 20%. It suggested the friend’s list might have included accounts that weren’t relevant to their business.
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Hack #2 Don’t overlook suggested friend’s underperformance
This hack is all about improving suggested Instagram for you performance, even when suggested friends’ lists are generating lower results than suggested users list. If you were wondering how much of an issue this could be, suggested friends lists can see suggested friend scores as much as 30% lower compared to suggested users.
The problem here is that you have no way of knowing apart from looking at the data in your suggested friend report or testing Instagram suggested for you versus suggested user performance.