Six-to-One Impact in Offline Stores

Based on two years of research conducted by retail marketing firm RevTrax, the study discovered that “for every $1 of e-commerce revenue generated from paid search, marketers can expect to see approximately another $6 of in-store revenue.”

In other words, paid search has 6:1 impact on offline sales over e-commerce. Because of the challenges of tracking consumer behavior online to offline, most of this has been invisible to marketers. Only now with the rise of smartphones and other methodologies is online-to-offline tracking becoming more widely available.

Between August 2009 and August 2011 RevTrax monitored millions of paid-search ads and consequent sales for its retail clients. To track in-store sales accurately RevTrax used landing pages with coupons and unique IDs:

• A paid search ad was displayed to a consumer
• The paid search ad led the consumer to a printable or mobile landing page displaying a coupon with a unique barcode
• The consumer redeemed the coupon inside a brick & mortar store
• Each coupon was tracked back to the online search (and the keyword)

Average Paid Click Worth $15 in Store

Using this methodology, RevTrax could conclusively determine in-store sales affected by paid search ads. Here’s how RevTrax’s findings illuminated the “value of a click” (where the average transaction size was under $200):

• The average click on a paid search ad generated approximately $15 of in-store revenue, with some merchants seeing as much as $28 of in-store revenue.
• Approximately 9% of clicks on a paid search ad generated an in-store sale, with some merchants seeing up to 26% of clicks on a paid search ad generating an in-store sale.

Again, what the company found was that paid search drove $6 in offline sales for every $1 in sales online. RevTrax thus argues that multichannel merchants who do not include in-store sales into the ROI calculation are potentially “undervaluing the paid search channel by as much as 85 percent.”

This is the first study to conclusively show the offline impact of paid search at this kind of scale, based on actual behavior rather than consumer surveys and self-reported data. The findings are pretty radical, with broad implications for search marketers and the industry as a whole.

Postscript: Here’s a bit more color and explanation from Seth Sarelson, COO of RevTrax, in response to a couple of questions I received about the study:

Clients are measuring these paid search campaigns at the keyword level and looking at brand keywords, competitive keywords, categories/products, etc. and the study uses a mix all these different types of executions to come to these results. I’m not sure that it’s clear to the person commenting that we’re talking about paid search only, not organic, so there’s certainly no guarantee that a brand is at the top of the paid search results for any keywords in a particular category.

One of the things that the study also mentioned is that many clients are reporting that 40-50% of customers acquired via paid search were new. This is big as it shows that this isn’t just an example of existing customers searching on branded terms looking for a deal.

It would certainly make sense for us to do a follow up that compares brand vs non-brand to address this specifically, as it’s an important point of distinction. I’m going to push for this internally.

As for PC vs Mobile, we’re working on a later study that will address these results, but most of what we’re looking at here is printable coupons from a PC.

Stock image from Shutterstock, used under license.

Conceptually none of this is entirely new. There are a range of “analog” companies and methods that measure retail foot traffic. However Euclid tries to bring online analytics’ sophistication to offline locations with smartphone tracking.

Offline Tracking with Smartphones

At least since 2008 people have been talking about using smartphones to track retail foot traffic patterns. And many companies are now trying to connect online and offline behavior with smartphones in various ways (e.g., check-ins, digital coupon redemptions).

Each physical venue or store location using Euclid installs a sensor that tracks people with smartphones entering the store. The company then provides a familiar type of dashboard, showing the various metrics it’s tracking. And yes, not everyone has a smartphone. But while smartphones are still not in the majority (43%), they will be in short order.

Euclid doesn’t track individual users. They see and deliver data in the aggregate.

Online to Offline: There’s a Larger Story

Euclid may or may not gain traction. But what Euclid represents is more important: a larger movement to connect online ads or promotions and offline behavior.

The venerable paper coupon or traditional call tracking have been the two primary methods historically used to measure the efficacy of advertising on in-store sales or ads-to-store behavior. More recently call tracking has been expanded to online advertising and digital coupons redemptions or check-ins (to a lesser degree) are starting to provide more visibility into the impact of online promotions on offline sales.

As another example of the online-to-offline tracking trend, search and social marketing platform provider Kenshoo is now monitoring Facebook and Foursquare check-ins (via APIs) to see if particular search or social ads produced in-store lift. The methodology isn’t connected to keywords but at some point you’ll probably be able to track paid-search keywords to in-store conversions.

Big Changes Coming with New Data

Credit card issuers and point-of-sale vendors are also starting to measure in-store conversions and tie those back to online promotions. There are some scary plans around credit card purchase tracking and the sale of personal data. And mobile payments/wallets will also eventually yield this “closed loop” data too — with varying degrees of anonymity.

Indeed, privacy will have to be negotiated in all these scenarios; and some of the “more aggressive” ones will probably need to be restrained by legislation. However the Euclid solution doesn’t fall into that privacy danger zone because it’s anonymous and aggregated.

The larger point is that within three years, lets say, the in-store success of online and mobile advertising will be much more visible than it is today. Indeed, the “offline” data becoming available to digital marketers via smartphones, credit-card matching and POS data is going to dramatically alter online marketing.

The numbers come from the 2011 State of Digital Marketing Report, which was compiled by Webmarketing123, a California-based online marketing agency. The company surveyed more than 500 U.S. online marketers in August and September; about two-thirds of all respondents identified themselves as B2B marketers.

Whether B2B or B2C, both groups of marketers agree that SEO has the biggest impact on lead generation. 57 percent of B2B marketers credit SEO as their primary source of generating leads, while 41 percent of B2C marketers said the same thing.

Both types of marketers say that website traffic is the primary way they measure the success of online marketing efforts. Brand awareness was at the bottom of the list for measuring success by both B2B and B2C respondents.

The survey asked a number of budget-related questions, including one about which channels get the majority of the marketers’ budgets. On the B2B side, one-third indicated that SEO gets the majority of their budget. But on the B2C side, more than 42 percent say that PPC gets the majority of their budget — about double the number of B2C marketers who said SEO is their top budget allocation.

Overall, 60 percent of respondents said they plan to increase their budget for social media marketing in 2012; 53 percent plan to increase their budget for SEO and 40 percent will increase their PPC budget.

Those increases in social media spending are likely field by another couple statistics from the survey: 68 percent say they’ve generated leads from either Facebook, Twitter or LinkedIn, while 55 percent have closed deals from social media leads.

The 2011 State of Digital Marketing Report can be downloaded from Webmarketing123′s website. You’ll need to provide name and contact information. There’s also an associated infographic with many statistic, which we’ve posted separately here: Infographic: Digital Marketer Views On SEO, PPC & Social Media.

But is there an opportunity to create the same sort of asset beyond search? Absolutely. Search retargeting can provide marketers with a totally transparent, multi-factor means to leveraging keyword expertise. And automation can play a big role in making it happen.

Evolution: Search Retargeting Today

Search retargeting has come a long way. While early attempts offered limited inventory, few keywords, incomplete reporting, inconsistent results, and scant optimization options, today’s advanced breed of retargeting solutions offers completely new optimization techniques and keyword management tools that both drive improved performance and provide insights for future marketing efforts.

All can be accomplished in a transparent, granular, multi-faceted manner to support high-volume, real-time bidding environments. In other words, today’s keyword decisions are happening at the speed of real-time bidding and at the massive scale of display advertising.

Why Search Marketers Should Care

This enormous scale and ability to optimize at the keyword-level appeals to the search marketer who already buys into optimization, and who seeks to scale their efforts beyond text-based search.

It takes them outside the silos of search and into their extended marketing and media mix, where they can leverage keyword intelligence in a much more holistic way.

Optimization Basics: Why They Matter In Search Retargeting 

To best leverage your keyword optimization knowledge when delving into search retargeting, you should tap into the basic building blocks of optimization that you leverage for search.

Doing so will go a long way to boosting the results of your retargeting efforts.

Just as in search, be sure to start with a broad set of keywords that are a reasonable reflection of your brand, your market, or your relative consumer demand.

The initial set can be based on search engine and campaign data, and include other terms that are likely to draw the consumer demand you seek.

In addition, be sure to include competitive terms as well as high-funnel category terms that may be cost prohibitive in search engine marketing. And remember to consider multiple aspects of the consumer path to conversion.

Option One: Manual Optimization

Once you’ve covered optimization basics, your search retargeting efforts will be on solid ground, ready for refinement. Significant performance improvements, whether measured in CTR, CPC, or CPA, can be made with manual optimization, which typically refines elements one at a time, without full consideration of how various elements interact with each other.

An example of single element manual optimization would be eliminating keywords that do not deliver the desired CTR, CPC, or CPA results. Other examples would be eliminating poorly performing sites, ad positions, creatives, times of day, etc. In addition to eliminating poorly performing keywords, additional keywords can be added to categories that are working especially well.

For example, if competitive terms are working well in a campaign, additional competitive terms can be researched and added. Finally, adjusting recency from 30 days to an instant might reduce volume, but also significantly decreases CPC / CPA.

The main advantage of manual optimization is that it is quick and easy. However, this method makes it difficult to account for the interaction of various campaign elements.

Option Two: Multi-Dimensional Automated Optimization

Automated optimization can provide you with multi-element approaches to refine and evolve retargeting efforts in real-time.

So what does it look like? Imagine that you are now able to change individual elements of any campaign – starting and stopping, yanking terms on the fly, in real time, based on observed performance of titles and descriptions, ad placement, exchange, bid, creative, frequency, per-period impression limits, etc.

However, because it’s automated, you don’t have to do all that work – the system does it for you. It essentially looks at variables that are impacting performance and decides whether or not to bid, how much to bid, and which ad to serve. And automation does it all in 30 milliseconds or less. In short, it will help you be quicker on your feet than ever before.

Below are just a few ways automated optimization can help: 

1. Maximize Performance. Because multi-dimensional automated optimization looks at the interaction of many campaign elements, performance can be improved over manual, single dimensional optimization techniques.
2. Improved Delivery. Single dimensional optimization requires more of a blunt instrument approach, in which some potentially valuable impressions are eliminated from consideration. For example, impressions targeted to a particular keyword may work well on some domains and not on others. Automated multi-dimensional optimization will allow continued delivery on the impressions with the keyword/domain combinations that are not performing well.
3. Save Time. Automated optimization eliminates the time required to manually pull reports, analyze them, and implement changes.
4. Dig Deeper. When you’ve attained a foundational understanding of your performance factors and your optimization outlook, you can then venture further into performance analysis. Doing so will allow you to look more deeply at combinations of individual components to identify weaknesses and opportunities for future efforts. Taking a more predictive approach here, you spot the correlations to help drive performance and help plan, budget, and manage future efforts.

Overall, marketers have a tremendous opportunity to parlay their keyword optimization knowledge into search retargeting.  The best way to successfully grow your efforts should include leveraging the power and scale of automation.

It will enable you to have aggregate learnings and cross-media trending data on your keyword assets at your fingertips — putting you in the best possible position to immediately and constantly tune your ROI, and model your path forward. It’s as close to predicting campaign success as you can come.

From the OneRiot blog post:

We’re delighted to announce that OneRiot has been acquired by Walmart.

The OneRiot team will now be joining @Walmartlabs – Walmart’s hub for the creation of new technologies and business models integrating social, mobile and retail for the next-generation of e-commerce.

And from the WalmartLabs post:

A few weeks ago, a small team from @WalmartLabs visited the offices of OneRiot in beautiful Boulder, Colorado. OneRiot has developed some pretty nifty technology that analyzes social media signals from popular networks like Twitter and Facebook to deliver ads that are relevant to consumers’ interests. As our teams debated the finer points of Big Data, Fast Data, and machine learning technologies, it became clear to us that we could find no better colleagues than the guys at OneRiot.

As a part of Walmart, we’re continuing to work with the intensity of a technology startup. Today I’m pumped to share the news that, within 30 days of that first meeting, we have closed a transaction to acquire the key assets of OneRiot. The technology team at OneRiot will move to Silicon Valley and become part of @WalmartLabs in September.

As I have written before, here at @WalmartLabs we’re doing some amazingly interesting and impactful work at the intersection of social, mobile, and retail. The technology at the core of what we do is the Social Genome, which enables us to connect millions of consumers with the best products based on their interests at any given moment. The OneRiot technology will enrich the Social Genome, and the OneRiot team adds to the already deep expertise we have around social data analysis.

In April, Walmart acquired the Kosmix search engine for WalmartLabs: Walmart Buys Former Search Engine Kosmix To Power Social & Mobile Shopping.

For the full year 2010 (graph below) paid search constituted 46 percent of total online ad revenues. If that’s still the case it would mean that Q1 2011 search revenues are roughly $3.35 billion.

Assuming about 25 percent growth overall this year, 2011 online ad revenues could reach $31 or $32 billion. That would mean 2011 search revenues would be nearly $15 billion.

Covario says Q1 spending was up 6% over the traditionally heavier Q4 period, and up 26% over Q1 of 2010. The huge year-over-year increase is mainly due to how weak spending was in Q1 2010.

Much of the growth is coming outside the US: Spending in both the Asia-Pacific and Europe-Middle East regions are up almost 50% over the past year. Consequently, Covario says, spending on Google is up 25% over the past year, spending on Yahoo is up 28%, and Bing — with its US focus — only saw a 4% increase in spending.

The report came out on the same day that the IAB released its full-year 2010 online ad revenue figures. Interestingly, there’s a $4 billion dollar discrepancy between the IAB paid-search figures ($12 billion) and the SEMPO estimate ($16.6 billion) for 2010. The SEMPO estimate is for “North America” while the IAB numbers are US only. The IAB estimated the whole of Canadian online advertising was worth $2.1 billion CAD in 2010, however.

Survey results throughout the report are analyzed in terms of the separate responses of search/ad agencies and advertisers (or “companies”), which have slightly different perceptions as well as spending patterns — although they’re consistent directionally with one another.

Here is a selection of the survey’s key findings:

Significant market trends:

• Mobile: 79 percent saw the rise of the mobile internet as “highly significant” or “significant” and this percentage has jumped 14 percent since 2010.
• Local: 43 percent of agencies say local search is “highly significant” and an additional 41 percent call it “significant”
• Behavioral: 78 percent rated behavioral targeting “highly significant” or “significant,” up from 68 percent the previous year
• 95 percent of respondents (advertisers/agencies) advertise on Google AdWords

Social marketing:

• 84 percent of agencies say they use Facebook for marketing up from 73 percent last year; 74 percent of agencies say their clients run PPC campaigns on Facebook
• 75 percent use Twitter to promote their companies or brands
• 52 percent use LinkedIn for marketing, and more than a quarter (27 percent) of companies now use it for PPC
• 52 percent of companies said social media has had a “moderate” (41%) or “huge” (11%) impact on their search-marketing activity in the last year vs. 80 percent of agencies
• There has been a significant increase in the percentage of companies saying  social media is primarily aimed at improving customer service and satisfaction, from 8% in 2010 to 13% this year. Fewer companies than last year say social media is about generating leads (-4%), but 3% more agencies than in 2010 say this is the main objective

Outsourcing on the rise:

• 44 percent of companies do SEO in-house, compared to 51 percent last year
• 38 percent of companies are doing paid search in-house compared to 47 percent in 2010
• 55 percent are doing social media marketing in-house, compared to 62 percent a year ago

Microsoft -Yahoo Search Alliance:

• 22 percent of companies and 27 percent of agencies consider the impact to be positive; 8 percent have a negative view. The top perceived benefits: better ROI, cheaper PPC prices, more traffic volume
• 43 percent said that the Microsoft -Yahoo Search Alliance doesn’t have an impact on their search marketing activity

Overall the survey is a great snapshot of the SEM industry and its major trends. These data are merely the tip of the proverbial iceberg, so to speak.

Paid Discovery has two price options: 10 cents or 25 cents per visitor, compared to five cents under the existing ad offering. But the extra cost includes priority ad serving — campaigns at the higher price levels that have deadlines will be served before other sponsored content. Another difference with Paid Discovery is the ability to show ads on mobile devices including the iPad, iPhone, and Android. Paid Discovery also offers more detailed analytics for advertisers, including sharing behavior across Facebook, Twitter and e-mail.

Like the existing StumbleUpon advertising, marketers can target their content to users based on age, gender, location and 500+ topics. And, the more the paid content is thumbed up, the more StumbleUpon will show it to users.

User Centric studied the search behavior of 24 “experienced users” of both Google and Bing, all between 18 and 54 years old. They were asked to do eight searches — four on Google (with Google Instant turned off) and the other four on Bing.

The results? Here’s a table version of the diagram above.

User Centric says there’s no significant statistical difference between the 28% of searchers who looked at Google’s right-side ads and the 21% who looked in the same place on Bing (as shown in row three above). Ads that appear above the organic results were viewed substantially more often than those in the right column and almost as often as the organic search results.

The various filters and refinements that both Google and Bing display on the left-side of the search results page were looked at even less than paid ads on the right: 18% for Bing and 17% for Google. Notably, time spent looking at Bing’s left column was more than twice on Google.

The main difference in activity was in time spent looking at organic search results; searchers on Google spent four more seconds looking there than Bing users did. The image example above is a search for “engagement ring” — both search engines provided a map with local results in the middle page along with numerous traditional “blue link” results. It looks like there may also be a news result near the top of the Google results. User Centric says one possible interpretation for the time difference is that users had more trouble finding the information they were looking for on Google, but it’s not clear what the reason was.

One other interesting stat: User Centric says only 25% of the study participants activated Bing’s automatic site previews, and each time it happened accidentally. Google also offers Instant Previews, but those require a click.

You can read more about the study on User Centric’s website.