Q4 Retail Search Strategy: CPC Strategy + HookLogic [On-Demand Webinar]

By Tinuiti Team

Engage Shoppers Where They’re Actively Looking to Buy

In this On Demand webinar CPC Strategy’s CEO Rick Backus and HookLogic’s VP of Search Media Steve Elson dive into how retailers and brands can drive conversions at key Retail Search channels by connecting retail inventory with high consumer intent.

Channels discussed in this webinar:


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Webinar Transcript:

Retail Search Techniques by CPC Strategy & HookLogic

Jon: I’m Jon from C.P.C. Strategy and welcome to today’s webinar on Q4 Retail Search Strategy. I’d like to start off today by giving you some context on why we’re having this webinar and what you can expect to learn from it.

Over the last several years, we’ve been seeing a pretty dramatic shift in digital product advertising. From working with Google directly and with our retail search management team working with client campaigns every day, we’ve gathered that pretty much the most important advertising channels for retailers and ecommerce-focused brands are those where retail search intent can be captured and converted. By retail search intent, I mean when a shopper expresses a high motivation to buy. This is pretty intuitive, because, of course, you want to be focusing your ad dollars where shoppers are actually buying.

As an example, I’ll compare a Google product listing edge which I use as the gold standard for C.B.C.-based product ad programs to a Facebook ad campaign. Of course, in this scenario, Google here can be subbed with a query on Amazon or any retail website like Walmart or On Google, a shopper might search for something like red leather pants and be served six or so image-based ads related to that. But on the flip side, in F.B.X., Facebook Exchange ad promoting an awesome inventory of red leather pants might be targeting someone who may be at some point in the past might have shown an inclination towards your product line.

The distinction here is that Google captures that shopper intent live in the moment and serves them a relevant product that basically connecting the consumer intent to relevant inventory. On the other hand, Facebook, as much as it’s been praised for being an effective and really evolving ad program, it doesn’t really capture that shopper intent when they’re most ready to purchase. That’s going to be the conversation for much of today, essentially how ecommerce merchants should be thinking about these retail search channels especially in Q4.

About CPC Strategy

A quick note about C.P.C. strategy, we’re a retail-focused search agency specializing in product data, shopping channels, product listing ads and text ads. Don’t worry, the webinar today is being recorded and we’ll send that out to you next week. The last thing is that this — we’ll be having a like Q&A at the end, so send in your questions in the questions chat box to the right or you can tweet it throughout the webinar using #CPCWebinar.

Our partner for this presentation is HookLogic. They’ve been a real innovator in product advertising technology, so we’re really happy to hear their perspective on the space today. Together, C.B.C. and HookLogic are really the first two agencies to start honing in on retail search as a discipline and really to start emphasizing the significance of connecting consumer intent with relevant inventory. We’ll be hearing from their V.P. of Search Media, Steve Elson. Steve is a search industry veteran and he actually just presented at iMedia Commerce which is a huge retail conference.

Expert Speakers

We have two very polished speakers today. I’m proud to announce, our first speaker for today is our C.E.O., Rick Backus. Rick is a retail and product advertising expert who speaks pretty regularly at big conferences, so I know we’ll enjoy his presentation coming up right now.

Rick Backus: I’m just going to jump right into today’s agenda. We are going to go over the new challenge of harnessing retail search intent. You’ll hear both Steve and I talk a lot about this concept of retail search intent. But I want to unpack it a little bit and help you understand what we’re actually talking about. Then I’ll briefly discuss Google P.L.A.s and the shopping engines and how they fit into your overall ecommerce strategy. We’ll have a couple slides to go over the challenges around the Amazon marketplace. We’ll discuss the retail search exchange by HookLogic. Actually, Steve will discuss the retail search exchange. I will go into some new findings on consumer behavior. Then both Steve and I will stick around for a live Q & A.

This is just a GIF that Jon put together of different searches on Google. The point is not to show you how Google works. I’m pretty sure that you’re familiar with the concept of Google and how to use it as a search engine.

Retail Search Intent

Rick Backus: The concept is that you want to match all of your searches with the intent of the shopper. Retail search intent is motivated online searching with the purpose to buy. Tools exist that allow brands and retailers to harness this retail search intent that weren’t here a few years ago and understanding retail search intent helps you connect your marketing to a shopper’s true intent. The basic premise here is about your customers. Retail search intent is really just an analysis of your audience. Your potential customers are giving you signals all the time with their online behavior. And if you follow the data, they’ll tell you when they’re ready to buy.

It’s challenging. It’s a lot more difficult than it used to be. It used to be you could kind of look at each individual channel and ecommerce, and as long as there was a positive R.O.I. for your text ads and your shopping engines were performing well and you’re gaining organic traffic, you could have this channel-centric view. Ecommerce has evolved. The competitive landscape has changed to the point where it’s really about your audience and understanding your customers.

That’s easy to do when you’re selling one product to your aunt and you can see how your aunt shops and she’ll get a catalog and you can watch her behavior and you may apply that same thing to the rest of your family or to your uncle. That concept of understanding their behavior is easy on the small scale. The challenge is when you’re trying to do that for thousands of customers and thousands of products. You really have to dig deep into understanding who your audience is, what their behaviors are, what signals they’re giving you. If you listen closely and you learn how to interpret those signals you can figure out when to put your products in front of them.

Google Analytics

Google Universal Analytics is a tool that allows you to get really in depth with individual audience members. You can look at the session for one person. The amount of analyses you can do in there is insane. I think adoption has been relatively slow in retail because there’s not a lot of retailers who actually understand retail search intent, and therefore, they’re not actively looking to increase the amount of data, because they don’t necessarily know how to interpret it. If you have the ability to understand your audience and you really feel like you have a handle on who they are, I highly recommend Google Universal Analytics. It’ll help you to look at not just the channels where you’re selling your products but the specific behaviors that are leading to your sales.

These are the channels themselves. If you have an understanding of your audience and you know how to interpret their behaviors, you need to get in front of them. For retail, Google comparison shopping engines, Amazon and the retail search exchange meaning other top tier retail sites, that’s here the customers are. If you now have the ability to interpret the retail search intent for your potential customers, now you need to go out to these channels and outsmart your competition who doesn’t necessarily understand those same signals.

Retail Search Channels

The factors that influence success on these retail search channels for product ads for C.P.C.-driven channels, you really want to focus on your product data. For Google P.L.A.s, for instance, there’s a quality score that Google has that is based on your feed. The higher your quality score, the lower C.B.C. that you could pay. Product data is something that I think a lot of retailers get bogged down by. They have this perception. Both brands and retailers have this perception that, “If I have a feed, I’ll send out my feed. It will get me on these channels. Once I’m on the channels, that’s when the real work begins.”

The challenge is actually putting together the most accurate product data up front and investing that time and, a lot of times, money into building out the product data, but it’s becoming more and more necessary to compete. The more accurate your product data is, the more that you have built out, the more that you can put your products in front of those customers when you’re interpreting their retail search intent. Enhanced product titles and descriptions, custom labels in your feed to segment your inventory however you want. That product data is really like the pre-season. It’s all that work up front to put you in the best position to succeed when the season starts.

Using that analogy, we’ll call the season campaign management. You want to leverage search term data to strategically deploy your products; implement advanced bid modifications by device, time of day or geo targeting; use negative key words to reduce your unprofitable spend; and increase or decrease exposure for custom inventory segments, for example, your top performing skews. If you understand what your top performing skews are and you understand the audience that’s going to purchase those skews, it becomes a lot easier to figure out how much to bid for those skews to get that exposure and how to make sure that you’re driving profitable traffic which is obviously the goal.

Amazon Marketplace

We’ll also go over the Amazon marketplace where the levers that drive by box ownership are different because the sale is taking place on Amazon and not on your website. The most important things for you to focus on are your technology partner, pricing strategy, competitive intelligence and feedback management. We’re going to jump into Google P.L.A.s and the shopping engines and how they, as channels, fit into your overall ecommerce strategy. Google over the last 18 to 24 months has dramatically changed the landscape of both average and ecommerce as a whole. They understand this concept of retail search intent and their development teams are actively working on trying to make sure that they’re showing products for queries that have a high transactional value.

They’ve done a good job so far of making sure that they’re not going to show your products for educational search terms when someone’s just doing research about ecommerce. In this instance, when it’s a more top of the funnel search like vacuum, meaning that it’s not a specific brand, this customer doesn’t necessarily know what they want yet. Google is experimenting a lot with their U.I. to show as many products as possible to help that customer figure out what their intent is and push them down the funnel so that they’ll make a purchase from your site. This is one test for doing what this product carousel. We’ve seen it applied to technology products like laptops, and now they’re starting to broaden it out to other categories like vacuums. Product listing now, it’s like Jon said, it’s really been the gold standard of product ads.

When you compare it to most other channels, it is the easiest channel to get a positive R.O.I., and in most cases it’s going to be profitable for the retailer. If you can’t figure out how to make product listing now that’s profitable, it’s either an indictment of the value proposition as a whole or you are just not managing the channel correctly. For the most part, if you’re in ecommerce you should be able to get Google P.L.A.s and Google shopping to be profitable for you.

Google Shopping

Here’s how you take advantage of Google shopping. These are the things to keep in mind over the next few months and we’ve put out a lot of content around Google shopping. We’ve done entire webinars around it. We’re an official Google shopping partner. I’m not going to go into too much detail here, but the main things that you want to know about Google shopping as that shopping campaigns will take over in late August and in the chat box, Jon is actually going to post a link of our guide that helps you with that shopping campaign transition. There’s new feed specifications that are set for September 30th. Q3 cleaning, you just want to make sure that your feed is set up for Q4. Monitor restricted products, some of the restricted products, especially in supplements and certain categories are — there’s not a complete list on Google and there’s suspensions that are very complicated to get yourself out of that position when you’re suspended.

Try to do a good job of making sure that there’s no keywords in your feed that potentially will get you products flagged. They won’t just take down the individual products, they’ll take down your entire feed. Also, broken mobile product pages, this is something that they announced recently where they’re going to trawl your mobile site, and if your mobile pages are not loading, they’ll actually take down your entire Google merchant-centered campaign. Take advantage of the new features, within Google shopping campaigns, you can now see impression share. Threes a bid simulator so that you can estimate bids and how much potential traffic that will drive you with the higher bid. In most cases, that’s trying to drive you to spend more money, but it’s still good to see the potential impact of raising your bids.

Mobile Traffic Bids

Then skew over reporting, we used to have to put together three or four separate reports and combine them just to see skew level data on Google shopping. Now, that’s all available directly through the Google shopping campaigns which makes the campaign management a lot easier. Then mobile bid modifications, traffic for mobile will be amplified. It will be amplified across the board, but you really want to make sure that your mobile bid is set appropriately. In most cases, the mobile traffic is going to convert at a lower rate than your desktop traffic or your tablet traffic. It makes sense to typically decrease your bids by — and in some instances we’ll do 50% or 75% decrease on mobile traffic. The exception here is if you have a really responsive site that converts just as well as your desktop and tablet traffic. In that case you really just want to look at the conversions and make sure that your mobile bid is set up appropriately. For most retailers, it makes sense to actually down bid the mobile traffic by somewhere between 50 to 75%.

The role of the shopping engines, I actually used to work at PriceGrabber. The background of our company, in the first few years, was based on PriceGrabber, at that time, it was Frugal and working with product feeds to go out to these comparison shopping engines. Unfortunately, there hasn’t been a lot of innovation in this space. They all were purchased by large private companies or private equity firms that really didn’t look to innovate. The only exception there is which was purchased by eBay. But for the most part, these channels haven’t innovated very much. It’s become more difficult for them especially after Google cut off their organic traffic to maintain profitability. At the end of the day, it is arbitrage.

They’re trying to look to carve out real estate mostly on Google and have you pay for that real estate. As long as there’s a difference between what you’re paying the comparison shopping engine and what they’re paying Google, there’s money to be made. That game is getting harder for them to play. The end result is that they’re raising C.P.C.s or they’ve had to raise C.P.C.s pretty dramatically. And it’s become difficult to maintain profitability on a lot of these channels. The way that we’ll approach them is it’s very rare for us to send an entire inventory feed to any one comparison shopping engine, but as an aggregate when you take PriceGrabber and and Shopsville [SP] and Mix Tag [SP] and you add them all up, they can often times be as large as a Google P.L.A. campaign.

And if you’re getting a 10 to 15% cost of sale on Google P.L.A.s, oftentimes, if you send only your best -selling skews or your brands that perform the best, you can get all of the shopping engines to add up as a channel to be close to the volume of Google P.L.A.s. In most cases, if you’re getting 10, 15% on P.L.A.s, you may get 20%, 25% on the comparison shopping engines. It still is a nice supplemental channel to grow your overall ecommerce sales.

Amazon Marketplace

I’m going to jump in real quickly to the Amazon marketplace. Once again, this is a GIF that shows you how Amazon works. I’m sure both of these GIFs have been very enlightening for you, how to do a search on Google and how to do a search on Amazon. The point is just for us to get you thinking about how your customers are using these channels. The Amazon marketplace is a friend to a lot of retailers. It’s a foe to a lot of retailers. There’s a lot of retailers who just put their head in the sand and say, “Amazon doesn’t impact my business. I’m not going to worry about it.” The reality is that just like Google, Amazon has an impact on every single ecommerce seller, whether you’re a manufacturer or you’re a reseller of products. You need to have some sort of strategy in place for the Amazon marketplace. That doesn’t necessarily mean selling on Amazon, but it may mean you send a small percentage of your products or you use Amazon as an outpost to list your products that you need to move quickly, because there’s a huge audience there.

Most Amazon sellers, even once they’re listed, they have trouble with figuring out what are the levers. There’s not a lot of information online around Amazon. The sellers that are doing really well aren’t really sharing those secrets. Unlike S.E.O. or paid search where there’s a ton of information online, it’s very easy to learn, the actual optimization strategies on Amazon are kept secret. And there’s not a lot of agencies or individual retailers who are really talking about that. Just real quickly, in terms of how you optimize your Amazon marketplace listings, it’s different whether you’re a brand yourself or you’re a reseller. In most cases the brands will either be approached by Amazon to have a direct vendor relationship or they’ll set up a third party marketplace account and compete with their resellers. Obviously, in that situation there’s a lot of moving parts and you have to make sure that you have a strategy in place to communicate with your resellers and let them know that you’re going to be selling directly.

As a reseller, it’s a lot different. It’s a lot more competitive and you can’t necessarily have a direct relationship with Amazon. Your technology selection is key. How are you going to fulfill your orders, your inventory management, multi-channel management platforms, the feed schema? All of this stuff is extremely important when you’re listing on Amazon, especially when you’re listing a large selection of skews. Then it’s an ongoing process, so feedback management. Reviews, both product reviews and seller reviews will have a huge impact on your overall sales. Monitoring sales ranking, competitive intelligence reports, re-pricing, shipping strategy, understanding how you win a larger percentage of buy boxes.

Our clients have come to us a lot over the years to try to help them out with their Amazon marketplace campaigns. We have previously turned away that business. Starting on August 1st, we are going to actively help our clients to interpret the signals on Amazon and improve their overall performance. The way that we’re approaching it is S.E.O. for Amazon, meaning that we’re going to try to drive impressions on products that already have a high buy box, order percentage and then conversion rate optimization for Amazon meaning that the sessions are high for an individual product, but the seller needs to improve the buy box percentage for those products. Coming August 1st, we’re going to have an Amazon marketplace consulting line of business to help our sellers grow their sales on Amazon.

Retail Search Exchange

Now, we’re going to jump into the retail search exchange by HookLogic. Steve will go over most of their solutions, but I just want to give you a brief introduction. The reason why we were excited about bringing them onto a webinar is because if you look at Amazon, obviously Amazon is driving a significant amount of sales. But as a whole, these top tier retail websites are, as an aggregate, driving significantly more sales than Amazon. If your strategy is just around Google and it’s just around Amazon, you’re missing a large piece of potential ecommerce sales by this retail search exchange. The way that retail search exchange works, and it will be illustrated here in the GIF is it will allow the individual brands to feature their products on these large websites.

You can see here, on Target, these featured products are getting a ton of exposure and you’re able, as a brand, to control which sites your products show up on. In addition to your Amazon strategy and your Google strategy, you now can figure out how to show up higher on Target or Walmart. The first page represents 91% of all product listing page views. Obviously, if you can get your product onto the home page of these huge websites, it’s going to put you in a position to expose your products to a much larger audience.

That’s it for my portion. Here’s the channels that we are talking about once again. We discussed Google, comparison shopping engines, Amazon, the retail search exchange. Really understand retail search intent. Understand how to promote your products to your individual audience. Once you have that understanding and you can interpret those signals, then when you go out to the channels, you’re able to outsmart your competitors and you’re able to bid on the keywords that you know are signals that your consumers are about to buy the product. Instead of just jumping on to all of the channels, you should put more energy and effort into really understanding that retail search intent.

In my experience, the clients that we have who are in the 50 million plus range in terms of total revenue, these are the types of conversations that they’re having. And the clients that are in the sub $20 million range, they’re still just trying to figure out the channels. I understand the limitations when you’re a smaller seller but there is a correlation there. To grow your business these days in ecommerce, you really need to understand the signals that your consumers are sending. And if you can do that, then when you go out to these channels you’re going to have a much more sophisticated strategy. I’m going to turn it back over to Jon who is going to introduce Steve.

HookLogic Speaker: Steve Elson

Steve Elson: Okay, thank you very much and thank you, Rick. We’re also very excited to be a part of this discussion. And I try to bring a new platform to the table that really serves a unique need within this whole landscape. As Rick was explaining, this is all about how retailers and brands, how ecommerce advertisers, really, can capture the power of putting products in front of shoppers who are displaying retail search intent and how powerful that is given the dominant role that online shopping and purchasing plays into the ecommerce environment.

Retail Search Exchange

As Rick mentioned, what we’ve done with the research search exchange is introduce a new kind of search, pay search media for part brands. This is a platform we created for product brand advertisers. and it speaks that you may need a brand who is selling through a retail distribution path. This is pay per click media for product brands whose products are primarily sold through retailers like Target, Babies “R” Us and Walmart, Sears and all those other ones that you saw. This is the case for essentially, nearly all product brands. Some, out there, have their own direct ecommerce operations. For the vast majority, their sales are essentially all done through these resale partners. Being able to, for the first time ever, pay for premium placement of your products in that environment is a huge win for product brands.

What this allows you to do, that is to promote retailer-specific inventory on each of the retailers that carry your products. And I’ll also have an example of that in a moment, but this is a native ad format. The type is the last point I made which is that as an advertiser in the retail search exchange, if you are promoting your — if you’re Gillette, promoting your shaving products, or Graco promoting your strollers, those products that you choose to promote are then promoted, are then displayed or featured only on the retailers where they are in stock and available for sale. Then the user, as you can see over here on this next page, has a clicking experience.

Here’s two more examples, a little bit easier to see. I’ll use an example of Corelle, a brand of dinnerware, and by leveraging the search exchange, they’re able to then have their products, when relevant, featured. An example on the left, a user did a search for bowls on Target, and above the organic listings of bowls, you see Corelle’s products are featured at the top. Then here’s an example on Walmart where the module is on product detail page, where someone is looking at some Gibson Home Dinnerware, a dinnerware set, and then they’re seeing over here, in this module, a whole bunch of matching products that Corelle offers. Then as I referenced, this is a click in, very native experience, where the product ads bring the user, bring the shopper to the product detail page on the retailer where they’re already choosing to shop. This really promotes the version. The shoppers are choosing their site. They’re particularly shopping around three sites, but they’re looking at sites that they are going to be very inclined to purchase from.

I should pause here for a moment because Rick brought up a really interesting point of view around Google when he said that P.L.A.s should be something that you can make profitable. And if not, then there may be something to revisit in the value proposition of the retailer. What’s really interesting about that is Rick and Jon and I were chatting as we were developing this webinar about the distinction between retailers using Google P.L.A.s and brands using Google P.L.A.s, and how the exception to that rule would be that if you are a product brand, it’s incredibly difficult to compete with your retail partners in Google P.L.A.

If I’m Graco and I want to sell my car seats, I am typically not going to see the same R.O.I. as Target or Walmart or Babies “R” Us when bidding on a generic search term like convertible car seat or infant car seat. Because if I’m a retailer and I gain the shoppers’ attention against the search term like convertible car seat, I win a conversion whether you buy a Grayco or Britax or any of the brands that I carry. But if you’re a direct product brand competing with these retailers, just like the C.P.C.s, you’re only going to win and get R.O.I. if they choose to buy your brand. Typically, the case is that a brand is not able to compete with retailers for these top placements in a Google P.L.A. environment which is what makes this program so unique for them.

We’ve got a network of retailers. We’ve got some of the most critical retailers in the U.S. participating on our network. It’s large, it’s growing. We are now adding some really exciting additions to our network later this quarter, before the holidays. We’re also launching a network in the U.K. later this quarter, so we’ll have some exciting announcements about network expansion. I’ve got just a slide or two about how the programs work, before we get in to some other interesting data. The campaign structure will be very familiar to those of you we’ve been using other programs, other retail search programs, because there are some similarities.

Local Product Categories

In the retail search exchange, an advertiser can organize campaigns around our local product categories. So keeping in mind that this is driving promotion across a large network of retailers which each have their own distinctive product taxonomy structures, what we do is we’re mapping those taxonomies to a global structure. Our campaign consists of an advertiser selecting which of those product categories that the advertiser wishes to promote. Not looking only can the advertiser pick categories, but the categories can then be defined even more specifically where an advertiser can select specific products. They can actually say, “Within my dinnerware, these are the 15 products that I really want to promote.” You can even set different skew level bids, where you can, as an advertiser you can bid at the category level, say I’m willing to pay 35 cents on dinnerware, but these are products that I’m going to pay 80 cents, because these are my newest line and I want to make sure those get extra visibility.

In terms of keywords, an interesting thing that we do, given that we’re working across retailers, is we actually automatically assign keywords to your products, to advertise your products, based on real shopper behaviors. What we’re doing is actually looking at quick stream data and learning, for each retailer, of what search terms are relevant for what types of product categories based on what products shoppers click on after entering search terms. Then we’re mapping those terms to an applicant’s products when they’re matching and relevant. To that list, we can supplement additional terms. So an advertiser says, “Here are some search terms that we want to make sure we are visible for,” we can add those terms as well.

One of those things that it does is it means that we’re really taking advantage of the unique shopping behaviors on each of our retailers. For example, somebody looking up notebook on Newegg, they’re looking for a laptop. But somebody looking up notebook on Staples is looking for a spiral bound paper product. We do that kind of publisher-specific keyword assignment.

Reporting Features

In terms of reporting, we talked a lot about how reporting can be a valuable — how reporting granularity in reports for optimizing your program. In the search exchange, we provide advertisements with all the standard delivery metrics. You’re going to get your impressions delivered, your clicks, C.P.C., E.Q.R., costs broken out by category as well by products. Then the real key thing that provides a ton of value to participants is that we’re actually providing sales data back on the program. Because we are plugged into the confirmation program pages of all of our publishers, we’re actually seeing the transactions, so we can tie back. We can show our advertisers what sales resulted from their program activity. They can actually look at it the sales guides, I’ve spent this much promoting my baby strollers and this much promoting my car seats, and how many sales did I get from that? We can report on volume sales and value sales, and then calculate what the return has been.

In this little example graph that you see, a piece of the report that looks at return on ad spend by category over different time trailing periods, you have seven-day, 30-day, 90-day. We always recommend looking at a measure of return on ad spend over a longer time period, that’s long enough to make sure you’re looking at stable data. Another thing that we do, because advertisers really are not only interested in looking at attributed sales but looking at incremental evidence, what’s the evidence of incremental sales, we can look at things. We’ve got a sponsored product impact report where we’re actually looking at the share that your sponsored product had of product page views as well as sales, so looking at sale volume and sale value. You can look and see, the products that you are promoting, how did their share of product page views, which is an indication of shopping and consideration, and how do their share of sales change during the campaign period? Really powerful measurements for understanding incremental impact of your program.

I’ve got a quick three slides of case study here. Intel is one of the [inaudible 00:40:41] that has been with us for over a year now, since shortly after we launched an early February of 2013, this network program. They’ve been with us for quite a while. One of the things that Intel really values about the program is the ability to essentially control merchandising throughout large retail channel. Intel is an ingredient brand, essentially. Intel doesn’t sell Intel laptops, but they partner with other manufacturers, other brands of laptops and tablets that carry Intel chips. While that’s a bit of a unique twist on the challenge in general, it’s the same challenge that — the challenge they share since they’re all product brands is that challenge of trying to drive sales through retail partners.

What they’re able to do is promote strategically important products. There’s tons of products that have Intel chips, but what they really want to do is drive sales of the premium products that are using their most innovative core technology. They will choose which tablets, which two-in-one devices they want to promote, and then they’re getting back from us skew level data on performance and return ad spend.

SKU Level Optimization

This is a part we do campaign a bit of data that just illustrates the points around skew level optimization. Our system does automatic quality scoring of products, and then buys the delivery towards those that are performing best from a click into conversion perspective. But we’re also looking at that data with our clients and making human decisions around what they want to prioritize. A quick point on this chart here, this is an exceptionally high performing program. Typically, we’ll see return on ad spend in the 500 to 1000% range, so 5 to 10x. This is a program where many of the skews were exceeding 1000% return on ad spend, which is what the scale converts on the left. It’s so crazy, you’ve got a few here that, while they’re low down, these are still skewed that are performing at a 500% return ad spend.

What this allows us to do, looking at it as a skew level, lets us work for our advertisers to make interesting decisions. You hear one that was relatively low volume and a relatively low R.O.S. and one that was also relatively low R.O.S. but a very high volume. So an advertiser can look at those different skews and actually decide, “Which ones do I want to continue to make eligible? Am I interested in continuing to have a lower return on ad spend that’s skew in the program that’s driving me huge volume sales and really helping me win new customers and which ones to optimize out of the program?”

In terms of overall results, it’s really exciting. Such industry really demonstrates the data that we’re able to provide advertisers about sales and their retail channel and how to look at incremental impact. What info they’ll be able to see in this program, this is from data earlier this year in Q1, they’re looking at a 41% lift in the share of product page views in these laptop categories that are reporting products. So there’s this huge increase in incremental consideration being driven. That translated into 7% lift, 7% increase in their share of sale volume and a 23% lift in their share of sales value. The reason it’s interesting you see that 7% incremental volume translating into 22% incremental value, and that’s because they were promoting these higher-end products that cost more.

We actually saw that if you were to cost — when you look at this data, you wanted to double check and make sure everything worked out. We were looking at the average price of products sold and the average price of an Intel chip product sold from there went up quite a bit and matched up, so it’s really interesting from the two that they could drive products and really drive sales of the right products through them. In terms of return on ad spend measure, you’re really looking at it from the perspective of cost efficiency. How much do they have to spend to drive those incremental sales? Not that much, so it performed really well for them, as well, in this regard, depending on the product and category they received between a 3 and 10X R.O.S. or roughly a $25 to $50 cost per unit sold.

Wrapping up this section, before we get into some interesting data and insights on how people are actually searching on retail sites, just bringing some core distinctions around the retail search exchange to understand that relative to some of those other platforms, this is for brands. We talked about this is for product brands to promote their products. They are sold across a network of retailers. It provides retail channel sales attributions, so actual sales that are being driven on those retailers. It’s really easy to sort of maintain. We have the product views already from each of the retailers in our network. None of our advertisers have to provide us with any assets, any product data. We’re already getting that information from the retailers, and the retailers are maintaining it and updating it, so there’s not that upkeep or skew data cramping that has to happen.

Native Ad Format

Then, it is this native ad format, so it’s the interesting part where you’re not driving shoppers to your website, you’re driving them to your products and targeting them to shop your products and buy your products with quick and convergence on those retailers. That wraps up that portion, and then there’s a final section here where we’re going to share some new findings, some insights into shopping behavior that we’re observing in these retail search environments. I’m going to jump into this last section.

One of the interesting things to think about when you’re considering search behaviors to recognize that when it comes to retail search, it’s not just about the query that was mentioned, the examples that Rick shared, focused on what we’re familiar with, where you enter in a search term and you get results. But on retailer sites, search listing pages and navigation listing pages or technology listing pages roughly split the traffic. This is aggregate across our whole network which includes, as you saw, sites like Target and Staples and Walmart and many other large ones. It’s very representative data. And this is showing what portion of all the product listing pages are right via search or navigation where people are using the product categories to drill down and get to the patio furniture they want to shop.

Filter Behavior

We see if they’re using both equally, and on top of that, there’s filter behavior. So 42% of all listing pages that we’ve seen on our network are filtered. This is really important. As a matter of fact, it’s one of the points that Rick made when he was giving some advice around how to participate in these programs, making sure that where you are the person or the party responsible for a clean data feed, making sure you got all the product attributes in there, [inaudible 00:47:37] your product shows up is eligible to be presented to shoppers when the shoppers are filtering, which actually dovetails into this next slide which is that, as probably many of you on the call here in this webinar have experienced yourselves, many people have come to distrust search and filtering when it comes to part discover.

This is an example on a retailer that I looked up bike belts. About half of the products on the top two rows, the results are not, in fact, bicycle belts. Now, we see, because it’s overlapped with this product, the brand name, but we’ve all experienced this to varying degrees of intensity where you notice products that are not really fitting what you searched for showing up in the results. What that leads most shoppers to conclude is that the reverse might also be true. They wonder, “Might I be missing out on products that do fit my search criteria?” This is actually showing a study that was done earlier this year by Compare Metrics and eChallenge Group which found that 73% of shoppers express this fear of missing out, they termed FOMO, fear of missing out, which is, literally, they’re afraid that to use search on retail sites or use filtering that they’re actually going to exclude products results that might be perfect for them and exactly meet their needs. So 73% of them, as you’d expect, said that they prefer using the browse page navigation tools when it comes to product discovery.

We see this [inaudible 00:49:02] in our own data, in our network. Drawing on our view into shopper behaviors throughout our retail network, what we see is that products that are found via search and filtering convert at about double the rate of parts that are found via navigation. It’s not the data navigation that the present against navigation pages is not powerful, because that is typically the preceding stage in the shopping process, so in that shopping cycle that some products might be hours and some might be days or even weeks or months in certain consumer electronics and other categories. Navigation is preferred for discovery when a shopper is determining the consideration set, and then search is more often leveraged when someone is supposed to be ready to purchase and they want to check out what they know they’re considering buying.

We see this in some of the other data we have, so we see a large portion of the highest converting searches including branded terms. Here’s an example of a brand, Timex, looking at their top converting search terms in our network by traffic, by volume of traffic, and you can see that only two of them were generic. The other ones involved some kind of branded term whether it’s Timex or the Ironman or the Weekender, these folks knew what they’re looking for.

This is a really powerful stat that Rick mentioned earlier that 91% of all the listing pages that we see here by shoppers are the first page of results. Less than 10% of the volume of listing pages are subsequent paged results. Just as we’ve all learned in other page search models, being on the first page is important. Then of course people pay attention top to bottom, left to right. These are some examples of the quick rates that we see by position regardless of the advertiser or product, just average for a site position where you’ll see a pretty significant change from the top slot to the next one down. And that’s true top to bottom, left to right. Not new information, but just helping to reinforce the value of having your products shown front and center where people can see them.

Q4 Trends

One last bit of data getting into Q4 trends. This is based on data that we saw in our retail network last Q4. We were looking at where this shopping activity really was spiking. It’s not just on Cyber Monday. One of the really interesting things we saw was that while Cyber Monday was the reigning champion in terms of the busiest on traffic and the highest converting base, we saw a bunch of these days that we call decision days where we saw traffic spikes as well as conversion spikes. In fact, with some of our retailers, especially those that were running some special Thanksgiving promotional activity, really bringing the sales forward, which is a trend we expect to see again this holiday season, trying to compete for your share of wallet as a shopper. We saw that Thanksgiving for many retailers actually was even exceeding Black Friday, which was online shopping and converting.

The other thing to point out is that we see significant week over week shopping traffic increases starting right away, November 1. Right after Halloween, we look at the first week of November, second week is significantly more shopping time than the first. Third is significantly more than that, so it’s a real steady ramp up of activity. Then another way to really just emphasize the power of being present in front of the active shoppers who couldn’t be higher on the retail search intent scale is looking at it this way which is taking the influence of the higher traffic along with the greater conversion rate that we’ve seen, and then looking at what that means in terms of really comparing the volume of transactions, the volume of purchasing and what’s happening on these decision days versus a typical day last year.

What you see is that Cyber Monday has 40 times the purchasing and these other decision days were in the 15 through 23 times range, so hugely important days obviously, but also gets recognized, that it’s not all about only Cyber Monday. There’s a whole period there that is incredibly important. I’m making note that this is November 24 this year, the Monday, before Black Friday.

Some key takeaways throughout that before we get into Q&A. Retail search data is critical for both retailers and brands. It’s more than enough evidence that proves that visibility of your products or visibility of your site is what drives consideration in sales. Advertisers need to leverage multiple platforms to address the reality of multi-tab shopping. We conducted some research that shows that on average, consumers are shopping 2.7 websites of retailers. I should say specific retailers. They might be looking at more websites. They might be referencing other information, other parts information resources. But specifically, they’re looking at nearly three retail websites per average online transaction. And it was more than half of people are looking at three or more sites. They are looking beyond just the first one.

Then brand advertisers can now leverage the retail search exchange for unprecedented targeting by retail search intent. When somebody is drilling down to a product category and filtering and when somebody is searching on Target or Staples, they’re indicating tremendous intent to make a purchase, and this is a new way for a product brand to take advantage of that and make sure they’re part of the considerations. Then lastly, just thinking about the holiday coming up, programs really should be optimized before the shopping starts to really kick off on November 1 and certainly well before the Monday before Black Friday. You really want to look at – I know that many of you who are in back to school categories are probably in the midst of that. That’s July, August, but you really want to look at September and October as your time frame for experimenting, optimizing and getting really comfortable with these programs, so you can be best situated to take advantage of the holiday season.

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