Behavior Flow: Analyze Price Comparison Shoppers
If you’re an online advertiser, the odds are good that the product or service you promote has a price tag on it somewhere.
That also means the odds are good that you’ve developed a healthy pessimism towards the capricious bargain-hunters who will blithely charge up dozens of paid clicks ad nauseam in the course of a jejune clicking-and-bouncing-and-clicking-and-bouncing bonanza before finally settling on a purchase from yourself or a competitor. We call them “Price Comparison Shoppers” – and they are a foe to be reckoned with.
Hello again advertisers! Today we’re going to examine the repercussions of “price shoppers” and other sponsored search behaviors that account for a “click-bounce-return” pattern – and what the advertiser can do about it. And trust me: you’ll definitely want to do something about.
Pretend, for a moment, that you are the real-world analogue of a digital proprietor: the humble shopkeeper. All you’re trying to do is keep the shelves stocked, run an honest business, and accommodate your customers with a marginally higher degree of success than the nearly identical shop across the street. So when it’s five minutes to closing time, and that customer that came in hours ago is still walking back and forth from the two shops, picking up and scrutinizing the wares before setting them down and walking back to the other shop without making a purchase, you may be liable to blow a gasket.
Quantifying Behavior Flow
Before we can assess the tactics needed to get undecided shoppers back into your store, we first must quantify the problem. To what degree might your web store or service be subject to a Click-Bounce-Compare-Return cycle? What percentage of your sponsored inbound traffic – the prospects you rightfully paid for – engages in this pattern? What portion of your conversions come as a result of your site ultimately winning a comparison cycle?
We already know from established observation and theory that it must be at least a decent portion. This is partly why display remarketing in PPC is so cost-effective. Since many shoppers will be returning to your site anyway, as part of this decidedly “millennial” comparison behavior, display remarketing nudges these shoppers to return with a 90% cheaper cost-per-click. Much better than investing the full market price for a second Search Network click in a row.
But to get real precision, we have to go to the data. And that means delving into Google Analytics, where we can access a litany of charts that are as useful as they are ugly. Before going any further, consider this pro-tip: I recommend widening your data timeframe even longer than you might think is necessary, in order minimize the α of your statistical significance.
To get the information we want, we’re going to have a look at your Behavior Flow diagrams and see what observations we can make. “The Behavior Flow report,” Google support will tell you, “visualizes the path users traveled from one page or Event to the next.”
See, while the pattern of users leaving and returning with different buying intent remains constant, the web pages and interactions these users make can vary widely from session to session.
The first Behavior Flow view I recommend would simply be the sessions graphed by inbound referral medium and returning session count. To find this view in Analytics, find the Behavior tab on the left sidebar and select Behavior Flow. In the upper-left green drop down, select Medium (or Source/Medium for even more segmentation). The Behavior Flow chart should now show you the most common pathways your users took navigating your site on first and repeat interactions, with drop-offs indicated in red waterfalls.
Behavior Flow: Asking the Right Questions
Already, this graph paints of portrait of user behavior with which advertisers and proprietors alike are often out of touch. We can now correlate inbound channels with user behavior trends. From these relationships, we can extrapolate something new about search intent and, ultimately, what might be a frustrating roadblock to a user’s intent causing them to bounce to a competitor. Sure, it may often be price – but it could just as often be a confusing shopping cart or a broken link.
This Behavior Flow view also provides an invaluable answer to the question, “Is the website doing its job well?” By which I mean: is the website going beyond mere information delivery and actually functioning – as a marketing platform – to move prospects through a qualifying funnel?
If your website is doing its job in this sense, you should see a pattern of users landing on information-oriented pages, like /FAQ and /about-us, and moving towards more action-oriented pages, like/cart and /freemium-download where your conversions live. (Yes, single-purpose microsites will be an exception here.) Even if those action pages don’t rise to the top until the third or fourth interaction, you should still see the pattern hold. Drop-offs are often completely justified, just to bring back those last few conversions on subsequent interactions.
Going Deeper: Session Flow vs Event Flow
Just because we’ve identified which winning pathways best funnel traffic to converting web pages in the long term, it doesn’t mean the buck stops there! We can also diagnose “Price Comparison Shopping” behavior AND propose a treatment if we look past the information visitors viewed and consider the interactions they made along the way.
To explore this further, I recommend switching your Behavior Flow metric over from Pages to Events. To do this, find the upper-upper-left white drop-down box, usually “Automatically Grouped Pages” by default, and select Events.
Along with the cool new color change, we can now see a corresponding pathway diagram of your Event actions, categories, and labels displayed in the same Medium versus interaction count structure arrangement as we had before with Sessions. Comparison between your Events Behavior Flow and your Sessions Behavior Flow unleashes some powerful questions:
How many users “impulse bought” on their first visit? Do all inbound channels boast a similar proportion? How many purchased on a subsequent visit? If the most common first Event a user triggers is something empowering two-way communication, i.e. phone, email, live-chat, have you determine what percentage of these is about price? How might this percentage compare to your customers’ thoughts on price in follow-up surveys?
Is there a session count after which a visitor is all but guaranteed to make a purchase? If so, and you’re experience more “soft” conversions in the gap between this count and the first session, it’s likely that Price Comparison Shopping is the culprit.
Taking Action: Capture the Sale Now
There are, of course, many more incisive questions and answers to be had from comparing these views, and I’m only able to opine on so many in this generalized format. And while your takeaway may very well be to reconsider your pricing strategy, you may be just as licensed to take steps to gather more information first.
For example, consider returning to the top of your inbound funnel. Are you mentioning pricing in your ad copy? Perhaps experiment with an A/B test concerning your pricing language. You cannot, unfortunately, experiment with advertising two different prices not available to the public at large, but you can test out, say, mentioning a coupon code for X dollars off in your “A” ads versus a control in your “B” ads. Your “A” ads may win fewer clicks but achieve more conversions from prospects less interested in the bottom dollar.
Or, you may wish to interject more potential conversion actions targeted at “priming” your first-time visitors. Incentives for a speedy checkout, limited time offers, dynamic remarketing ads, drip email campaigns, and real-time communication channels like chatbots and webRTC feeds (my favorite is the Amazon “Mayday Button”) are all proven methods other advertisers have taken to preclude a lengthy bounce cycle.
Can Marketers Adapt to Changing Behaviors?
Ultimately, the insights accrued from Behavior Flow may clarify the role of Price Comparison Shopping among your PPC traffic and alleviate some of the associated frustrations, but it doesn’t diminish the importance of catering your marketing to be responsive to every customer touchpoint, on every platform, on every channel.
“Omnichannel” appears to be more than just a buzzword. Customers increasingly demand contextualized experiences that follow them across what you may have previously considered independent marketing channels, unified only by bizarrely complex Assisted Conversion pathways for which SEM is only one of several stepping stones. The rise of Price Comparison Shopping isn’t a phenomenon unique to your business; it’s the new paradigm of shopping, especially in eCommerce, and it’s here to stay.
One more thing for certain: marketers who pay attention to more than just their numbers-in/numbers-out, disregarding actual user behavior patterns in the interim, are going to find themselves on the wrong side of natural selection in the coming years.
Please oblige me and don’t become one of them. Go check your Behavior Flows now!