CRO & Testing

If you ever ran a highly trustworthy and positive a/b test, chances are that you’ll remember it with an inclination to try it again in the future – rightfully so. Testing is hard work with many experiments failing or ending up insignificant. It’s optimal to try and exploit any existing knowledge for more successes and fewer failures. In our own practice we started doing just that.

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The m-commerce share of total e-commerce spending continues to grow at a steady pace. In the US, as many as 71% of total digital minutes are spent on a smartphone or tablet. In Indonesia, 91%.

All of which confirms that launching dedicated mobile lead generation campaigns is no longer an option but a necessity.

This post will discuss how one online retailer used mobile popups to start targeting and converting their smartphone visitors, what strategies they’ve used and which ones delivered the strongest results.

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It’s no secret that email is the most effective acquisition channels for any marketer. In fact, according to Campaign Monitor, for every $1 spent, email marketing generates $38 in ROI.

But with all the noise today, it’s getting harder to get noticed. Today, it’s not enough to send the right emails; you need to send the right emails at the right time.

And that’s exactly why smart marketers rely on drip marketing.

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Search Engine Optimization (SEO) is one of the biggest levers that a business can use within their acquisition strategy as part of their Growth goals.

You’re likely familiar with the different Growth frameworks like AARRR (Acquisition, Activation, Retention, Referral, Revenue). It all starts with Acquisition. Getting users familiar with your product by visiting them on your site or in app. One of the biggest channels to do that is through organic search traffic. Over the last years I’ve led different marketing and growth (SEO) teams that were focused on driving as much (relevant) traffic as possible from search. Here’s what I’ve learned.

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If you’re invested in improving your A/B testing game, you’ve probably read dozens of articles and discussions on how to do a/b testing.

In reading advice about how long to run a test or what statistical significance threshold to use, you probably saw claims like “Always aim for XX% significance” or “Don’t stop a test until it reaches YYY conversions” – where XX% is usually a number higher than 95%, and YYY is usually a number higher than 100.

You might also have heard it’s best to come up with many variants to test against the control to improve your chance of finding the best option.

No matter what rule is offered, such advice seems to rest on the assumption that there is a one-size-fits-all solution that works in most situations.

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