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3 min to read

Product pages & Google Shopping. A customer journey battleground.

More shoppers are now starting their journey at the product level of a website than almost anywhere else because of Google Shopping. But this results in some less than desirable user behaviour. Read on to learn more...

The Rise of the Product First Journey

Driven by the growth in programmes like Google Shopping, more shoppers are now starting their journey at the product level of a website than almost anywhere else, and is a trend reflected across both desktop and mobile devices.

In fact, in the retailers we benchmarked for this audit, up to 46% of shopping sessions began in such a way, with an average across the spread of 36%. For practically all retailers, this is a greater percentage of sessions than those that begin at the home page, which is a starting point for just over 20% of customer journeys on average.

[insert images]

On that basis it’s fair to say that if you’re investing in Google Shopping as a key channel, then more shoppers are starting their journey with you ‘product first’, than through any other touchpoint on your site.

Why is this a big deal?

This is an important segment to recognise, as your product pages are seldom designed to be the first point of a journey, and typically don’t get anywhere near the amount of attention that home pages or high level category pages get when it comes to merchandising, enrichment, testing, customisation, optimisation, analysis or anything really. This means you’re driving more shoppers into your site through the place that’s least optimised to give them a good first impression.

There is good news…

The good news you probably already know. That due to the high purchase intent, the conversion rate on Google Shopping and product entry level traffic is generally very good. Certainly at the higher end of most retailer’s spreads. As you can see in this comparison.

Combined with lower cpc’s and fast times to purchase, the ROAS on Google Shopping traffic is impressive, with many retailers seeing 1.5-3.5x the ROAS they see in generic/non brand paid search activity.

This has encouraged many retailers to divert greater portions of their spend towards shopping search, to the point where some retailers are now investing as much as 75% of their total budgets into it.

The bad news…the engagement is very poor!

The engagement level of shoppers starting their journey at the product level through Google Shopping is shockingly poor. Or to put a silver lining on it…rife with massive opportunities for improvement. Two things really stand out here that jar with this channels outstanding conversion potential.

1. Shopping traffic is almost twice as likely to bounce!

Despite strong conversions on Google Shopping traffic, the lost opportunity is far higher. Overall ecommerce retailers are routinely seeing bounce rates of nearly 70% or more on Google shopping traffic, which begins its journey at the product level.

This is nearly twice the level of bounces when compared with shoppers coming to the site directly or from other traffic sources like generic PPC, which typically begin their journey at the home or category level of a site.  Given how much of this is bought in traffic it highlights a huge amount of wasted spend.

2. Shoppers from Google Shopping don’t browse much either!

On average, and largely as a byproduct of the high proportion of bounces, a session initiated from Google Shopping averages a number of pages viewed of between 2.5 & 2.7 per session. Even when bounces are removed the average page views jumps little more than a single page. This indicates that among the remaining number that try to engage, people either buy fairly directly or drop back out after attempting to browse.

So why is Google Shopping search so ‘Buy or Bust’?

The impressive conversion rate and ROAS of Shopping search and product entry level traffic is at stark odds with its high bounce and low page engagement rate, unlike any other channel.

Sure we’d expect some bouncing and a spread of page view activity that varies over the funnel, and there are often clear reasons for a high bounce rate. Mercenary shoppers, slow loading pages, mobile usage etc. But all the data across many retailers, suggests that shopping traffic either buys, or takes a cliff face drop off the edge of the site, and far more so than when compared to similar channels.

Something else is surely afoot here, and it’s when you dive into the data that it becomes clear that the customer journey is amiss.

Product listings might get the clicks, but shoppers want choice & range!

Products in Google Shopping may generate impressive click-throughs that are highly qualified. They are however seldom product specific searches. Detailed query anaylsis shows, that a high concentration and wide mix of category and type related searches are producing the clicks on product listings. This indicates that shoppers want a far broader and higher level choice than the product offers. You can see an example of this in a couple of analyses from our audit below.

Example a: This GIVENCHY distressed logo jumper in black is displayed in the google shopping box and yields impressions and clicks on a wide array of terms. However, what we can see in the treemap is that those terms which are referring traffic are far more generalised than the product that yielded them. In this case, the retailer had ample inventory to satisfy most of these queries at the higher level of their site. Yet this product produced a 76% bounce rate. Even if you were to swap out products for better sellers, it still wouldn’t solve the main issue of the query spread.

GIVENCHY Black distressed logo jumper

Example b: This Samsung 21 inch monitor is a strong performer in Google Shopping for another retailer. It’s a strong seller, but exhibits a very high bounce rate of 71%. The treemap of queries once again hints strongly at why. It is deriving much of its traffic from searches that are related to its many attributes, and its category parentage.

Samsung S22D300HY 21.5″ HDMI LED Monitor

What’s very evident from these, and the dozens of examples we uncovered in our benchmark audit, is that product pages are the first touchpoint in a huge proportion of customer journeys, where the shoppers are expressing a clear desire for choice somewhere in the range above the product they came in on. All in all that might not be such a bad thing, were it not for the next point.

Product pages are quite the cul-de-sac!

To compound Google Shopping sending huge amounts of generic traffic to product pages, those same product pages box the shopper in and make it difficult for them to un-narrow the product out to the relevant groupings of choice that they want.

Whereas conventional browsers can easily back-click to the category they were exploring, our shoppers landing via Google Shopping are limited to using breadcrumbs and a handful of ‘Related’ product recommendations to expand their choice, or face the daunting plunge back to the home page to start again.

Breadcrumbs don’t leave as good a trail as we think they do!

The faithful breadcrumb falters in many product first journeys, as even if a customer were to look towards it to try and un-drill the product, they often make the journey harder, rather than easier.

For example, any shoppers clicking on these listings below, and expecting to be able to easily drill upwards to more of the same, would find the breadcrumbs taking them to somewhere between a category of hundreds of products and the store entrance.

Furthermore, several sites didn’t even reflect a clear breadcrumb at all. A sure fire way to encourage a bounce.

The breadcrumbs on these product pages don’t leave much of a trail for shoppers

Product recommendations don’t fare much better

Product recs are another accepted means of advancing the customer journey with relevant alternatives. However, once again these are often starkly at odds with the intent of shoppers who have landed on the particular product, and want to see more.

The below examples were taken from the product pages listed in the above ‘red lace dress’ example.

While these products may be a good suggestion for someone who has browsed that product as a part of their wider exploration, they are not going to meet the shopper where they’re at, in terms of their intent and desire to see more red lace dresses.

Red lace dress hunters would be sorely let down by most product recommendations.

We need to optimise the journey, not just the campaigns!

What’s very clear from analysing Google Shopping search, is that whilst a strong portion of traffic is spot on and converts very well indeed, much of it is wholly misplaced not just in terms of the product choice, but at the product level as a whole.

Customers come in on products with an explicit need for choice, and in many cases that need is very broad. In most cases however, sites are practically (albeit inadvertently) pushing them back out by making it difficult to explore simple choice.

So you can squeeze the campaign, the products, the feed, your agency, maybe even Google, to try and tighten up the wastage in your shopping campaigns, but when you look at the whole journey, it’s not difficult to see where the problems are, and why shoppers are inclined to follow the path of least resistance and bounce straight back to shopping.

By giving shoppers relevant options that align with what they want to buy, we can encourage them over the threshold of our product pages to explore the wider offer, reduce the chance of a bounce and increase the likelihood they’ll have the FoundIt! moment that will crystallise a sale.

It therefore makes sense to pay more attention to the journey we are giving shoppers when they arrive at this level, and make an internal Journey Optimisation part of the external marketing programme.

In our next post…

..we’ll be staying on this theme, and looking directly at how FoundIt’s journey optimiser recognises the intent of your Shopping search visitors, and reshapes your product first journey to improve choice, reduce bounces, and increase conversion by as much as 40%. If you can’t wait till then though…drop us a line.

We are seeing increases in conversion and reduction in bounce rate by implementing FoundIt! at the product level of the site from Google shopping ads. If you’d like to know more, download the datasheet :

3 min to read

Is ‘Ecommerce Assist’ a thing? It should be!

This thought provoking blog examines key questions about ecommerce attribution models and makes suggestions for the future.

Ask a digital marketer about attribution...

You will likely get the following response:

We know the last-click model is flawed, but it’s the best model we’ve got!

Which basically means that the bulk of the credit for any given sale will likely go to the final touch point that delivered the order. But is this fair if conversion has been improved through onsite factors. Why should PPC get all of the credit?

Let’s look at the typical buying cycle of trying to purchase a summer jacket online, and look at how many channels that may have contributed to the experience.

All we know at this point is that I’m optimistic for some sunshine, and that this winter jacket I’ve been relying on for the last few months, can be put to the back of the wardrobe.  I head over to Google and I type in the imaginative keyword ‘mens summer jackets’.

The first thing that I notice are the options in Google Shopping. Handy, because I don’t really know what I’m after yet and I now have some examples to trawl through for a bit of inspiration, and I click on a few to take a better look.

However, I’m still tyre kicking, and want to see a bit more before I commit. I liked the look of the ‘Chore Jacket’ (never even knew ‘Chore Jacket’ was a thing?), and now feel ready to drill deeper.

Before I know it, I’ve been back and forth on Google images; blog reviews; Amazon, and even eBay. Not sure how that happened?

After reviewing my options, I decide to finally make a purchase from who have the item that I want. (No prizes for guessing that I made that site up for the purposes of this post).

I key in the brand name, click on the paid link and go straight to the website. Now where on this colossal site is the item that I saw previously on the web. Once on the site, I find my jacket but get side-tracked by a similar item offered in the product recommendations. Before I know it, Ive clicked through and have decided to buy that jacket instead. I’m just about to put in my credit card details when I decide to have a look for a voucher code before I commit.

Result! I find a voucher code after a quick search on Google. And the purchase is made.

So where does this now sit regarding attribution. Well the voucher site company takes the credit for the deal via the attribution report as it’s only fair as they were the last touch point. Right..?

Over the course of my buying journey, I had interacted with Google Shopping, PPC, SEO, Blogs, Marketplace sites, Affiliates, and On-site technologies. Yet the last-click attribution model can only provide one winner.

Who deserved the sale, and more importantly should one channel get ALL of the credit?

Regardless of how you look at it, the one channel we know that won’t see any of the credit, is the onsite technology that increased the conversion rate and resulted in the purchase.

Ecommerce isn’t alone. In the sales world the glory has always gone to ‘the closer’.  But what about the touch point that first gained the prospects interest? And what about the media that built up their enthusiasm for the proposition before ‘the closer’ walked into the door to seal the deal?

In sports such as football, the accolades have historically gone to the goal scorer, that made the vital last touch before the ball crossed the line. What about the 10 players behind him, who created the opportunity? What is the value of their contribution?  Which is probably why football now recognises the ‘assist’ as a key metric. Players that can continually create these scoring opportunities for their team mates are known for their value, and it is appreciated that the goals would not have happened without them.

Do we show the same recognition for the ‘Ecommerce Assist’? Is it even a thing?

The danger of not finding a way to truly recognise the ‘Ecommerce Assist’ is that it can commercially harm performance in a big way. By de-valuing the key contributors of a sale, they can soon be fighting for survival as budgets are slashed. It’s a controversial argument, but in the example above, did the voucher site actually de-value the sale by offering a discount where a purchase was already emotionally decided upon? And then get financially rewarded as the victorious channel in the process?

Would it be profitable across the business if we decided to do more of this ‘voucher’ activity as they always seem to be ‘the closer’. Maybe yes/maybe no. However, it’s not as simple as looking at one isolated sale, when these brands see thousands of transactions every day.

What would happen if we cut the budgets for Google Shopping, and non-branded keywords in PPC, because we felt they weren’t converting well enough? Would the sales continue to come in without those channels in the mix?  These old questions crop up within the digital marketing world and are often re-visited when the question of budgets comes around. Yet there is still ground to be made on getting the attribution model just right.

However, there is another challenge with attribution and the concept of the ‘assisted conversion’ that is even more prevalent in the digital marketing landscape right now.

Are we focusing on the wrong metrics?

Performance marketers know that their channels need to perform and deliver great ROI in order to justify their budgets. But could we be so focused on the channels at an individual level that we miss the bigger picture?

If a technology ends up inadvertently increasing conversion rate of a PPC campaign by 20%, who gets the credit?

Now initially, this may sound like an easy riddle to solve. But depending on the structure of the marketing department, the opportunity to increase the performance of a channel can be overridden by the fear that it may ‘appear’ to reduce performance. This ‘appearance’ is created by sharing the credit for that increased performance.

This is a bit like a football striker wanting to play up front alone, so that he doesn’t have to share the scoring opportunities. Even though having two potential scorers could provide a clear advantage to the wider team and enable more goals.

In both the ecommerce and sport scenario, the increase in performance is created by the ‘synergy’ of more than one component working together. Are we not missing a trick by worrying too much about which one is the final victor?

Maybe it’s time that the ‘Ecommerce Assist’ is taken more seriously and becomes a thing!

So what could the future of attribution look like?

The first key point, is to recognise what channels/ technologies played their part in a sale.

If a sale can be attributed to a single campaign with no influence from anywhere else then great. We all like simplicity and this is a nice easy pathway to report upon. However, more than likely a large portion of sales involves a discovery, an exploration and a decision-making phase. All of which see the shopper crossover multiple channels along the buying process.

Each touch point along the way needs to fulfil its objective of gaining attention, maintaining attention, educating the shopper, and committing them to the purchase. Working like a conveyer belt as each communication promotes the shopper to the next phase of their shopping journey until they reach for their credit card.

If they had never heard of your products and services would they have still bought it? Definitely not!

If you didn’t have adequate content for the shopper to explore your propositions, would the shopper still have bought it? Possibly, though we’d be relying on them already knowing exactly what they wanted and being highly motivated.

And if the shopper was on your site and engaging in your content would they definitely make a purchase? Well we all know that optimising conversion rate is an art and any professional with retail experience will tell you that products rarely sell themselves. You have to walk over and engage the shopper to get them over the line. Your ecommerce platform is no different.

Which is why the thinking around the attribution model needs to evolve to recognise each part of the puzzle that contributes to the sale. Old school direct marketing campaigns may have been much simpler to test and measure, as you could record upon them in isolation. However, just because the digital world allows channels to operate in synergy it doesn’t mean that a better way of reporting cannot be achieved.

We just need to give it some thought.

Test and Measure

These words will not be new to anybody in marketing. But ultimately there is only one way to determine the true value of campaigns, and that is the data.

If you remove this particular traffic source then what happens to the overall sales?

If this technology wasn’t on the site then what would the impact be on the conversion rate?

And so on, and so forth.

Most big brands are already engaged in numerous A/B split tests and multi-variant tests on a regular basis. But strangely these results don’t always get trickled back into the marketing teams that work on the attribution reports to use.

Moving forward, we see an environment where attribution takes into account the two major factors of ecommerce acquisition which is:

Sales = Traffic x Conversion Rate

There are channels which get eyeballs to the website. And there are onsite strategies and technologies which complete the purchase. They have to work hand in hand.

If you think of it like rowing a boat, these 2 entities are your oars. If one is pulling harder than the other then you’re going to end up rowing in circles and getting nowhere. But pulling together they can take you anywhere you want to go.

Most shoppers will need an element of convincing. If you’ve ever been behind the scenes of a car showroom you will learn that there are a team of car sales people that are there to engage people looking to buy a new car. And they’ll have a league table in their back office of which rep sells the most cars.

They know that selling is an art, and that the car isn’t going to sell itself. It is their job to hold the buyers hand and walk them through the process of making their purchase. It is no surprise that salespeople that can maximise the revenue from their traffic are considered very valuable and rewarded accordingly.

So do you think the credit of that car sale will ultimately go to the poster that first introduced them to the dealership? Well it played it’s part in getting the interested prospect through the door but there was a lot of work still to be done to confirm the sale.

3 min to read

Fenwicks launches FoundIt! via AB Test for Proven Results

As with most of our new clients we recommended Fenwick launch as a 4-6 week AB test. We do this because we want clients to be just as confident as we are in the results. Discover more about how we work...

Learn how Fenwicks is creating bespoke shopping journeys with FoundIt!

Earlier this Summer Fenwick launched FoundIt’s unique AI-based customer journey optimisation platform as part of an ongoing commitment to offering the very best shopping experience for their customers.  Fenwick know that by aligning their ecommerce site experience with what matters to their customers they’ll be able to stay on top of trends and evolving catalogues, ultimately driving more sales.  FoundIt! helps Fenwicks create these tailored ecommerce experiences easily without a burdensome integration or heavy impact on page load times.  

As with most of our new clients we recommended Fenwick launch the implementation as a 4-6 week AB test.  We do this because we want clients to be just as confident as we are in the results.

An aside about how FoundIt! works

The FoundIt! platform makes it easier for customers to find and buy items by using a unique blend of AI designed to optimise the shopping experience on large ecommerce websites.  Unlike traditional personalisation, we don’t depend on cookies or an individual’s browsing history, instead looking at natural language trends. FoundIt! goes far beyond product recommendations, instead specialising in dynamically re-architecting website navigation around the customer in real-time.

By showing shoppers more of what they are likely to buy via dynamically created navigation we increase the likelihood of a sale.  Therefore, increasing revenue is the ultimate goal of one of our AB tests and we usually measure this via an increase in Revenue Per User (RPU).  RPU rises by virtue of conversion rate increasing. Conversion Rate is the primary metric that we base the statistical significance of our test results on.

A bit more on the AB testing methodology

We apply Foundit!'s dynamically generated navigation across Fenwick’s website (focusing on product pages, search pages and category pages).  Because users are more likely to find the products they are looking for the conversion rate rises. Fenwick are using Google Optimize as their AB testing platform and the results will be analysed in Google Analytics as well as with Foundit!'s statistical significance calculator.

The test is not yet complete but early results are promising

The Fenwicks implementation includes Foundit!'s product list page and search results page drill down navigation with images, as well as our product details page "you may also like" image carousel. This also includes a variation of the image carousel on out of stock pages where it is placed at the top of the page to help users navigate to other products.  FoundIt! Is a flexible tool which can be used to improve many common ecommerce journeys.

Andrew Jayes, Digital Director at Fenwick, says,

“Having used Foundit! in my previous role I have witnessed first-hand what an impact their journey optimisation technology can have on increasing revenue. Their method of implementation via AB test is risk free for Fenwick and I know I can trust their team to do a great job for me.”

Commenting on the project, Warren Cowan CEO & Founder of Foundit! says,

“Fenwick is a British institution who are committed to a great customer experience, that is why I am thrilled we're working with them on their retail website to optimize customer journeys & grow sales.  I can’t wait to see the results from this AB test – watch this space!”

3 min to read

FoundIt! Achieves Retail Suppliers Qualification System Accreditation from Helios

Great news - FoundIt! has achieved RSQS certification proving compliance with a set of industry wide standards, offering assurance to existing partners and online retailer alike.

FoundIt! Achieves RSQS Accreditation

If you are reading this then you probably already know that FoundIt! are an AI-based customer journey optimisation platform dedicated to helping large ecommerce websites improve their navigation and increase their revenue.  

We are very proud to have achieved RSQS accreditation earlier this year after going through a vigorous assessment process in support of our partnership with John Lewis & Partners.

Julian Pettit, SEO Team Manager at John Lewis commented "It's imperative to John Lewis that all our partners are RSQS accredited.  The accreditation gives us and others reassurance that essential standards are being met. FoundIt! are fast, reliable and secure, this accreditation proves it beyond measure.”

RSQS registration is a fundamental certification process which proves that FoundIt! are in compliance with a set of industry wide standards including corporate responsibility, sector specific legislation, information security and GDPR; providing confidence and assurance to all existing partners and any online retailer.

“The certification is an exciting development for FoundIt! because it shows that we are committed to being an excellent and responsible supplier.  From top customer service to compliance and ethical standards.  It means retailers can be assured that we do our work properly.” says Chris Dunn, FoundIt!’s COO.

Want to download our certificate – click here  [ADD LINK]

More information about the RSQS programme can be found at the Helios website.

3 min to read

78% Increase in Conversion Rate using FoundIt!

The story of a 78% increase in conversion; where FoundIt! helped more users find what they were looking for, faster and more easily than all the other methods on the site. Including search, facets, filters, and sorts!

78% Increase in Conversion Rate at IronmongeryDirect

IronmongeryDirect are committed to making sure that their online customers get the same valued experience that agents are giving from their call centre.

As the largest supplier of specialist ironmongery to builders, joiners and shop fitters for over 40 years, it was essential that the website was easy to navigate, and inventory of 16,000 specialist products could be found.

The challenge for IronmongeryDirect was that every product category was unique, more so than the average retailer. Therefore, the one-size-fits-all nature of a website didn’t consider the niche specialism of products carried with the many different types, finishes and sizes etc.  This led to them giving all the options in facets and navigation and hoping that the customer has the time, energy and inclination to find what they were looking for.

Surpassing all KPI’s:

  • Grew Revenue by 7%
  • Conversion Rate by 78%
  • Impacted 27% of user journeys

Find out more by downloading the full case study now.

“We have been extremely pleased by all of the uses that FoundIt! gives us! Our online customers are finding products quickly and easily using FoundIt! smart navigation. In addition, FoundIt! has also become invaluable within our call centres, as a way for our agents to guide customers around our product range; finding alternate products and navigating between sections. Not only that but as an unplanned consequence, FoundIt! has become so useful in our call centre that we have incorporated it into company-wide staff training, in teaching our product ranges and learning what our customers actually want!”

Charlie Carlton, Ecommerce Manager, IronmongeryDirect

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