AWA digital’s Marketing Coordinator, Nicole Major, explores the latest conversion optimisation tools and industry news with insights provided by our Chief Operating Officer Johann Van Tonder.
This month I explain how EyeQuant is using artificial intelligence to measure the impact of adverts; review a new user engagement analytics tool from Kissmetrics; take a look at how Survey Monkey Genius uses insights to create better surveys; and report on two new features from Google Optimize.
Google Optimize increases test limits
Many Google Optimize users have said that running more tests more often is a top priority when it comes to improving online experiences. As a result of this feedback, Google Optimize has increased the experience limit from three tests at a time to five.
A new installation diagnostics feature has also been launched to automatically check that Optimize has been set up correctly before a test is started as this has been preventing customers from running tests.
We love it when tool developers listen to customer feedback and respond.
Johann Van Tonder, Chief Operating Officer for AWA digital
"At AWA we believe that test velocity - the number of split tests per year - is a key success driver in optimisation. This increase in the number of testing slots enables Google Optimize users to move faster towards insights and conversion uplift. Considering recent findings by eConsultancy that the optimal number of a/b tests per month is 3 - 5, Optimize now hits the sweet spot."
A smart way to measure the impact of ads
Every day, millions of online display ads are served to consumers all over the world, but it’s not always easy for advertisers to know where their ad appeared, due to complex bidding schemes, or even if it was on the user’s screen long enough to be noticed.
Added to that, many ads don’t get viewed because they simply aren’t eye-catching enough. To address this, EyeQuant has used artificial intelligence to build a prototype algorithm that instantly rates ads from 0-100 in terms of their impact.
Many marketers trust their design team to judge the impact of a creative, but this is not always a safe bet. In fact, the EyeQuant algorithm shows that ads running for some of the world’s top brands are highly inconsistent and include examples of low scoring creatives.
For example, these two pieces of creative used to promote Dove products show a huge variable in the results, with the ad on the right being ten times more effective at drawing the eye.
Tests showed that the new algorithm had an 85 per cent correlation with the results of a user study based on 500 real people using eye-tracking and online panel research, so users can be confident that it provides powerful and accurate feedback about display ad campaigns.
User engagement is elementary with Sherlock
Sherlock is a smart new tool from Kissmetrics designed to help SaaS companies measure and quantify user engagement.
This user engagement scoring application is described as an analytics product with a purpose – to help make user engagement a centralised metric that drives actions across the entire SaaS operation.
Sherlock works by giving SaaS teams the ability to create a customised engagement scoring model for their product. The journey starts by sending product usage data to Sherlock via Segment.com, then key product events are weighted based on their importance to overall engagement.
This enables web owners to rank users based on their engagement level with the product, giving a valuable understanding of engagement at an account level.
User engagement is the lifeblood of the entire SaaS model and this new tool will enable marketing teams to make the metrics accessible in all key tools, such as Salesforce, Slack and Segment.
Using insights to create better surveys
SurveyMonkey Genius brings together artificial intelligence, survey expertise and machine learning and automatically applies these insights to help users create better surveys.
This new tool automatically reviews a survey design and questions, providing a score estimating the completion success rate and the estimated time it will take to complete based on best practice. This is a great way to identify any red flags in advance, so users can send a survey out with complete confidence.
Valuable data starts with the right question type and SurveyMonkey Genius can help users work out which type – such as slider or star rating, multiple choice or matrix – will provide the best results. It can also help write answer choices by auto-filling a set of pre-written options proven to capture accurate data.
This new tool harnesses the power of more than 20 years’ of learnings collected by SurveyMonkey to highlight specific questions and areas of a survey that can be improved. This will help to maximise response rates and collect the best quality actionable data.