Expert Interview: How to Optimise for Ecommerce Conversions

4 Minute Read

I sat down with Ben Smith, personalisation consultant from Bunting to discuss how brands can properly implement ecommerce conversion rate optimisation tactics in order to drive traffic and convert more sales.

What does a typical day look like in your role?

Hi I’m Ben, and my role is a personalisation consultant. That means that day-to-day I’m dealing with customer inquiries, from the very start point of them getting in contact, to all the way down to post-sale support.

The in-between bits of that mostly falls to the implementation of personalisation campaigns (at a high level).

A pretty healthy blend of sales, web development and account management. You know, a lot of calls to explore how Bunting will fit into existing marketing strategies, and often advising clients about the next stages of the strategy.

Why do brands need your help?

The key issue that an awful lot of eCommerce brands are facing is the ability to keep visitors on their website.

A lot of brand will drive traffic by using Google Adwords for example, but hit a brick wall when the customer gets to the site. You know, studies show that an end-user makes a decision to stay on a site within 3-7 seconds.

Is the site poorly designed? If you accidentally click on a product is there any other product options? Is the site slow to load?… these can all be a real big issue for brands because potential customers will not stick around for a frustrating experience. This is when conversion rate optimisation comes into play.

Is this a uniform process? Does it work for everyone?

All optimisations are an evolutionary process; things that work for some may not work for others. But that’s what we are here to figure out. Our approach helps to laser-focus the success of Bunting and ultimately raise our clients conversion rate optimisation.

It is absolutely not a cookie cutter approach, we tailor the process to ensure that not every piece of functionality is implemented. You have to work closely with individual accounts, so you can assess the individual needs of the organisation. I guess it’s personalised personalisation.

Once we have the plan scoped out, a multi-pronged attack can be undertaken. This is so the self-service aspect of Bunting can be utilised by the end-user. We have a managed service element which allows us to build the most complete and powerful Bunting functionality… very well-themed product recommendations for example.

Talk us through the stages of Conversion Rate Optimisation?

With a pretty small window of opportunity, there are several quick wins that are proven to lower bounce rates and encourage more conversions. At a high level, these can be summarised as:

• Algorithmically-generated product recommendations (especially in the case of product pages)
• Urgency messaging social proofing.
• On-site personalisation (if a user arrives on the site through a targeted campaign the theme and feel will be pertinent to that specific campaign)
• Discount incentives (subtly incentive for customers to make/increase a purchase)
• Site-exit pop-ups (a little more nuclear, asking for feedback about a site’s performance)

All of these processes are split tested and analytically driven, so me and the user can really get the most out of the tool’s performance. Once the tests have been properly established, the final piece of the puzzle is to put live the results that held a high level of confidence.

These tests contribute to the key idea that Bunting constantly evolves, conversion rate optimisation never stays stagnant.

You’ve dealt with a lot of accounts… is there any stand-out examples of success?

An awful lot of the success stories that I can think of seem to be coming out of the eCommerce fashion industry right now. A lot of outlets have product recommendations as part of the platform, like Magento for example; we find that they often miss the mark in how effective they can really be.

We are always able to ascertain a lot of information by running split tests against the default program recommendations with Bunting AI. As an example, a clienthad a platform that was making them sales, but the ‘out the box’ capabilities of Magento were proving to be a hinderance for user retention.

Brands like Lakeland Leather and Rebellious Fashion also generated significant ROI by replacing their default recommendations… results saw a massive uplift in conversions.

It is often as simple as improving user-experience. These brands often need some help in making mobile usability more effective. This has sometimes been as simple as fixing the ‘add to basket’ button at the bottom of the screen so it was more persistent (as opposed to having the ‘call to action’ button way below the fold), we know this irritates users.  

That’s a wrap Ben, any more advice?

Well eCommerce is a busy place these days. There are loads of things to help push your brand that little bit further.

Bear your customers journey in mind at all times and try to mimic that face-to-face, great customer service feel. Get in touch with me at Bunting if you want to start optimising!