Posted by TheMozTeam

Google is all about serving up results based on your precise location, which means there’s no such thing as a “national” SERP anymore. So, if you wanted to get an accurate representation of how you’re performing nationally, you’d have to track every single street corner across the country.

Not only is this not feasible, it’s also a headache — and the kind of nightmare that keeps your accounting team up at night. Because we’re in the business of making things easy, we devised a happier (and cost-efficient) alternative.

Follow along and learn how to set up a statistically robust national tracking strategy in STAT, no matter your business or budget. And while we’re at it, we’ll also show you how to calculate your national ranking average.

Let’s pretend we’re a large athletic retailer. We have 30 stores across the US, a healthy online presence, and the powers-that-be have approved extra SEO spend — money for 20,000 additional keywords is burning a hole in our pocket. Ready to get started?

Step 1: Pick the cities that matter most to your business

Google cares a lot about location and so should you. Tracking a country-level SERP isn’t going to cut it anymore — you need to be hyper-local if you want to nab results.

The first step to getting more granular is deciding which cities you want to track in — and there are lots of ways to do this: The top performers? Ones that could use a boost? Best and worst of the cyber world as well as the physical world?

When it comes time for you to choose, nobody knows your business, your data, or your strategy better than you do — ain’t nothing to it but to do it.

A quick note for all our e-commerce peeps: we know it feels strange to pick a physical place when your business lives entirely online. For this, simply go with the locations that your goods and wares are distributed to most often.

Even though we’re a retail powerhouse, our SEO resources won’t allow us to manage all 30 physical locations — plus our online hotspots — across the US, so we’ll cut that number in half. And because we’re not a real business and we aren’t privy to sales data, we’ll pick at random.

From east to west, we now have a solid list of 15 US cities, primed, polished, and poised for our next step: surfacing the top performing keywords.

Step 2: Uncover your money-maker keywords

Because not all keywords are created equal, we need to determine which of the 4,465 keywords that we’re already tracking are going to be spread across the country and which are going to stay behind. In other words, we want the keywords that bring home the proverbial bacon.

Typically, we would use some combination of search volume, impressions, clicks, conversion rates, etc., from sources like STAT, Google Search Console, and Google Analytics to distinguish between the money-makers and the non-money-makers. But again, we’re a make-believe business and we don’t have access to this insight, so we’re going to stick with search volume.

A right-click anywhere in the site-level keywords table will let us export our current keyword set from STAT. We’ll then order everything from highest search volume to lowest search volume. If you have eyeballs on more of that sweet, sweet insight for your business, order your keywords from most to least money-maker.

Because we don’t want to get too crazy with our list, we’ll cap it at a nice and manageable 1,500 keywords.

Step 3: Determine the number of times each keyword should be tracked

We may have narrowed our cities down to 15, but our keywords need to be tracked plenty more times than that — and at a far more local level.

True facts: A “national” (or market-level) SERP isn’t a true SERP and neither is a city-wide SERP. The closer you can get to a searcher standing on a street corner, the better, and the more of those locations you can track, the more searchers’ SERPs you’ll sample.

We’re going to get real nitty-gritty and go as granular as ZIP code. Addresses and geo coordinates work just as well though, so if it’s a matter of one over the other, do what the Disney princesses do and follow your heart.

The ultimate goal here is to track our top performing keywords in more locations than our poor performing ones, so we need to know the number of ZIP codes each keyword will require. To figure this out, we gotta dust off the old desktop calculator and get our math on.

First, we’ll calculate the total amount of search volume that all of our keywords generate. Then, we’ll find the percentage of said total that each keyword is responsible for.

For example, our keyword [yeezy shoes] drew 165,000 searches out of a total 28.6 million, making up 0.62 percent of our traffic.

A quick reminder: Every time a query is tracked in a distinct location, it’s considered a unique keyword. This means that the above percentages also double as the amount of budgeted keywords (and therefore locations) that we’ll award to each of our queries. In (hopefully) less confusing terms, a keyword that drives 0.62 percent of our traffic gets to use 0.62 percent of our 20,000 budgeted keywords, which in turn equals the number of ZIP codes we can track in. Phew.

But! Because search volume is, to quote our resident data analyst, “an exponential distribution,” (which in everyone else-speak means “gets crazy large”) it’s likely going to produce some unreasonably big numbers. So, while [yeezy shoes] only requires 124 ZIP codes, a keyword with much higher search volume, like [real madrid], might need over 1,000, which is patently bonkers (and statistical overkill).

To temper this, we highly recommend that you take the log of the search volume — it’ll keep things relative and relational. If you’re working through all of this in Excel, simply type =log(A2) where A2 is the cell containing the search volume. Because we’re extra fancy, we’ll multiply that by four to linearly scale things, so =log(A2)*4.

So, still running with our Yeezy example, our keyword goes from driving 0.62 percent of our traffic to 0.13 percent. Which then becomes the percent of budgeted keywords: 0.0013 x 20,000 = tracking [yeezy shoes] in 26 zip codes across our 15 cities.

We then found a list of every ZIP code in each of our cities to dole them out to.

The end. Sort of. At this point, like us, you may be looking at keywords that need to be spread across 176 different ZIP codes and wondering how you’re going to choose which ZIP codes — so let our magic spreadsheet take the wheel. Add all your locations to it and it’ll pick at random.

Of course, because we want our keywords to get equal distribution, we attached a weighted metric to our ZIP codes. We took our most searched keyword, [adidas], found its Google Trends score in every city, and then divided it by the number of ZIP codes in those cities. For example, if [adidas] received a score of 71 in Yonkers and there are 10 ZIP codes in the city, Yonkers would get a weight of 7.1.

We’ll then add everything we have so far — ZIP codes, ZIP code weights, keywords, keyword weights, plus a few extras — to our spreadsheet and watch it randomly assign the appropriate amount of keywords to the appropriate amount of locations.

And that’s it! If you’ve been following along, you’ve successfully divvied up 20,000 keywords in order to create a statistically robust national tracking strategy!

Curious how we’ll find our national ranking average? Read on, readers.

Step 4: Segment, segment, segment!

20,000 extra keywords makes for a whole lotta new data to keep track of, so being super smart with our segmentation is going to help us make sense of all our findings. We’ll do this by organizing our keywords into meaningful categories before we plug everything back into STAT.

Obviously, you are free to sort how you please, but we recommend at least tagging your keywords by their city and product category (so [yeezy shoes] might get tagged “Austin” and “shoes”). You can do all of this in our keyword upload template or while you’re in our magic spreadsheet.

Once you’ve added a tag or two to each keyword, stuff those puppies into STAT. When everything’s snug as a bug, group all your city tags into one data view and all your product category tags into another.

Step 5: Calculate your national ranking average

Now that all of our keywords are loaded and tracking in STAT, it’s time to tackle those ranking averages. To do that, we’ll simply pop on over to the Dashboard tab from either of our two data views.

A quick glimpse of the Average Ranking module in the Daily Snapshot gives us, well, our average rank, and because these data views contain every keyword that we’re tracking across the country, we’re also looking at the national average for our keyword set. Easy-peasy.

To see how each tag is performing within those data views, a quick jump to the Tags tab breaks everything down and lets us compare the performance of a segment against the group as a whole.

So, if our national average rank is 29.7 but our Austin keywords have managed an average rank of 27.2, then we might look to them for inspiration as our other cities aren’t doing quite as well — our keywords in Yonkers have an average rank of 35.2, much worse than the national average.

Similarly, if our clothes keywords are faring infinitely worse than our other product categories, we may want to revamp our content strategy to even things out.

Go get your national tracking on

Any business — yes, even an e-commerce business — can leverage a national tracking strategy. You just need to pick the right keywords and locations.

Once you have access to your sampled population, you’ll be able to hone in on opportunities, up your ROI, and bring more traffic across your welcome mat (physical or digital).

Got a question you’re dying to ask us about the STAT product? Reach out to clientsuccess@getSTAT.com. Want a detailed walkthrough of STAT? Say hello (don’t be shy) and request a demo.

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Posted by bsmarketer

Content promotion isn’t tweeting or upvoting. Those tiny, one-off tactics are fine for beginners. They might make a dent, but they definitely won’t move the needle. Companies that want to grow big and grow fast need to grow differently.

Here’s how Kissmetrics, Sourcify, Sales Hacker, Kinsta, and BuildFire have used advanced content promotion tips like newsjacking and paid social to elevate their brands above the competition.

1. Use content to fuel social media distribution (and not the other way around)

Prior to selling the brand and blog to Neil Patel, Kissmetrics had no dedicated social media manager at the height of their success. The Kissmetrics blog received nearly 85% of its traffic from organic search. The second biggest traffic-driver was the newsletter.

Social media did drive traffic to their posts. However, former blog editor Zach Buylgo’s research showed that these traffic segments often had the lowest engagement (like time on site) and the least conversions (like trial or demo opt-ins) — so they didn’t prioritize it. The bulk of Zach’s day was instead focused on editing posts, making changes himself, adding comments and suggestions for the author to fix, and checking for regurgitated content. Stellar, long-form content was priority number one. And two. And three.

So Zach wasn’t just looking for technically-correct content. He was optimizing for uniqueness: the exact same area where most cheap content falls short. That’s an issue because many times, a simple SERP analysis would reveal that one submission:

(image source)

…Looked exactly like the number-one result from Content Marketing Institute:

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Today’s plagiarism tools can catch the obvious stuff, but these derivatives often slip through the cracks. Recurring paid writers contributed the bulk of the TOFU content, which would free Zach up to focus more on MOFU use cases and case studies to help visitors understand how to get the most out of their product set (from the in-house person who knows it best).

They produced marketing guides and weekly webinars to transform initial attention into new leads:

They also created free marketing tools to give prospects an interactive way to continue engaging with their brand:

In other words, they focused on doing the things that matter most — the 20% that would generate the biggest bang for their buck. They won’t ignore social networks completely, though. They still had hundreds of thousands of followers across each network. Instead, their intern would take the frontlines. That person would watch out for anything critical, like a customer question, which will then be passed off to the Customer Success Manager that will get back to them within a few hours.

New blog posts would get the obligatory push to Twitter and LinkedIn. (Facebook is used primarily for their weekly webinar updates.) Zach used Pablo from Buffer to design and create featured images for the blog posts.

Then he’d use an Open Graph Protocol WordPress plugin to automatically add all appropriate tags for each network. That way, all he had to do was add the file and basic post meta data. The plugin would then customize how it shows up on each network afterward. Instead of using Buffer to promote new posts, though, Zach likes MeetEdgar.

Why? Doesn’t that seem like an extra step at first glance? Like Buffer, MeetEdgar allows you to select when you’d like to schedule content. You can just load up the queue with content, and the tool will manage the rest. The difference is that Buffer constantly requires new content — you need to keep topping it off, whereas MeetEdgar will automatically recycle the old stuff you’ve previously added. This saved a blog like Kissmetrics, with thousands of content pieces, TONS of time.

(image source)

He would then use Sleeknote to build forms tailored to each blog category to transform blog readers into top-of-the-funnel leads:

But that’s about it. Zach didn’t do a ton of custom tweets. There weren’t a lot of personal replies. It’s not that they didn’t care. They just preferred to focus on what drives the most results for their particular business. They focused on building a brand that people recognize and trust. That means others would do the social sharing for them.

Respected industry vets like Avinash Kaushik, for example, would often share their blog posts. And Avinash was the perfect fit, because he already has a loyal, data-driven audience following him.

So that single tweet brings in a ton of highly-qualified traffic — traffic that turns into leads and customers, not just fans.

2. Combine original research and newsjacking to go viral

Sourcify has grown almost exclusively through content marketing. Founder Nathan Resnick speaks, attends, and hosts everything from webinars to live events and meetups. Most of their events are brand-building efforts to connect face-to-face with other entrepreneurs. But what’s put them on the map has been leveraging their own experience and platform to fuel viral stories.

Last summer, the record-breaking Mayweather vs. McGregor fight was gaining steam. McGregor was already infamous for his legendary trash-talking and shade-throwing abilities. He also liked to indulge in attention-grabbing sartorial splendor. But the suit he wore to the very first press conference somehow managed to combine the best of both personality quirks:

(image source)

This was no off-the-shelf suit. He had it custom made. Nathan recalls seeing this press conference suit fondly: “Literally, the team came in after the press conference, thinking, ‘Man, this is an epic suit.’” So they did what any other rational human being did after seeing it on TV: they tried to buy it online.

“Except, the dude was charging like $10,000 to cover it and taking six weeks to produce.” That gave Nathan an idea. “I think we can produce this way faster.”

They “used their own platform, had samples done in less than a week, and had a site up the same day.”

(image source)

“We took photos, sent them to different factories, and took guesstimates on letter sizing, colors, fonts, etc. You can often manufacture products based on images if it’s within certain product categories.” The goal all along was to use the suit as a case study. They partnered with a local marketing firm to help split the promotion, work, and costs.

“The next day we signed a contract with a few marketers based in San Francisco to split the profits 50–50 after we both covered our costs. They cover the ad spend and setup; we cover the inventory and logistics cost,” Nathan wrote in an article for The Hustle. When they were ready to go, the marketing company began running ad campaigns and pushing out stories. They went viral on BroBible quickly after launch and pulled in over $23,000 in sales within the first week.

The only problem is that they used some images of Conor in the process. And apparently, his attorney’s didn’t love the IP infringement. A cease and desist letter wasn’t far behind:

(image source)

This result wasn’t completely unexpected. Both Nathan and the marketing partner knew they were skirting a thin line. But either way, Nathan got what he wanted out of it.

3. Drive targeted, bottom-of-the-funnel leads with Quora

Quora packs another punch that often elevates it over the other social channels: higher-quality traffic. Site visitors are asking detailed questions, expecting to comb through in-depth answers to each query. In other words, they’re invested. They’re smart. And if they’re expressing interest in managed WordPress hosting, it means they’ve got dough, too.

Both Sales Hacker and Kinsta take full advantage. Today, Gaetano DiNardi is the Director of Demand Generation at Nextiva. But before that, he lead marketing at Sales Hacker before they were acquired. There, content was central to their stratospheric growth. With Quora, Gaetano would take his latest content pieces and use them to solve customer problems and address pain points in the general sales and marketing space:

By using Quora as a research tool, he would find new topics that he can create content around to drive new traffic and connect with their current audience:

He found questions that they already had content for and used it as a chance to engage users and provide value. He can drive tons of relevant traffic for free by linking back to the Sales Hacker blog:

Kinsta, a managed WordPress hosting company out of Europe, also uses uses relevant threads and Quora ads. CMO Brian Jackson jumps into conversations directly, lending his experience and expertise where appropriate. His technical background makes it easy to talk shop with others looking for a sophisticated conversation about performance (beyond the standard, PR-speak most marketers offer up):

Brian targets different WordPress-related categories, questions, or interests. Technically, the units are “display ads, but they look like text.” The ad copy is short and to the point. Usually something like, “Premium hosting plans starting at $XX/month” to fit within their length requirements.

4. Rank faster with paid (not organic) social promotion

Kinsta co-founder Tom Zsomborgi wrote about their journey in a bootstrapping blog post that went live last November. It instantly hit the top of Hacker News, resulting in their website getting a consistent 400+ concurrent visitors all day:

Within hours their post was also ranking on the first page for the term “bootstrapping,” which receives around 256,000 monthly searches.

How did that happen?

“There’s a direct correlation between social proof and increased search traffic. It’s more than people think,” said Brian. Essentially, you’re paying Facebook to increase organic rankings. You take good content, add paid syndication, and watch keyword rankings go up.

Kinsta’s big goal with content promotion is to build traffic and get as many eyeballs as possible. Then they’ll use AdRoll for display retargeting messages, targeting the people who just visited with lead gen offers to start a free trial. (“But I don’t use AdRoll for Facebook because it tags on their middleman fee.”)

Brian uses the “Click Campaigns” objective on Facebook Ads for both lead gen and content promotion. “It’s the best for getting traffic.”

Facebook’s organic reach fell by 52% in 2016 alone. That means your ability to promote content to your own page fans is quickly approaching zero.

(image source)

“It’s almost not even worth posting if you’re not paying,” confirms Brian. Kinsta will promote new posts to make sure it comes across their fans’ News Feed. Anecdotally, that reach number with a paid assist might jump up around 30%.

If they don’t see it, Brian will “turn it into an ad and run it separately.” It’s “re-written a second time to target a broader audience.”

In addition to new post promotion, Brian has an evergreen campaign that’s constantly delivering the “best posts ever written” on their site. It’s “never-ending” because it gives Brian a steady-stream of new site visitors — or new potential prospects to target with lead gen ads further down the funnel. That’s why Brian asserts that today’s social managers need to understand PPC and lead gen. “A lot of people hire social media managers and just do organic promotion. But Facebook organic just sucks anyway. It’s becoming “pay to play.’”

“Organic reach is just going to get worse and worse and worse. It’s never going to get better.” Also, advertising gets you “more data for targeting,” which then enables you to create more in-depth A/B tests.

We confirmed this through a series of promoted content tests, where different ad types (custom images vs. videos) would perform better based on the campaign objectives and placements.

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That’s why “best practices” are past practices — or BS practices. You don’t know what’s going to perform best until you actually do it for yourself. And advertising accelerates that feedback loop.

5. Constantly refresh your retargeting ad creative to keep engagement high

Almost every single stat shows that remarketing is one of the most efficient ways to close more customers. The more ad remarketing impressions someone sees, the higher the conversion rate. Remarketing ads are also incredibly cheap compared to your standard AdWords search ad when trying to reach new cold traffic.

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There’s only one problem to watch out for: ad fatigue. The image creative plays a massive role in Facebook ad success. But over time (a few days to a few weeks), the performance of that ad will decline. The image becomes stale. The audience has seen it too many times. The trick is to continually cycle through similar, but different, ad examples.

Here’s how David Zheng does it for BuildFire:

His team will either (a) create the ad creative image directly inside Canva, or (b) have their designers create a background ‘template’ that they can use to manipulate quickly. That way, they can make fast adjustments on the fly, A/B testing small elements like background color to keep ads fresh and conversions as high as possible.

(image source)

All retargeting or remarketing campaigns will be sent to a tightly controlled audience. For example, let’s say you have leads who’ve downloaded an eBook and ones who’ve participated in a consultation call. You can just lump those two types into the same campaign, right? I mean, they’re both technically ‘leads.’

But that’s a mistake. Sure, they’re both leads. However, they’re at different levels of interest. Your goal with the first group is to get them on a free consultation call, while your goal with the second is to get them to sign up for a free trial. That means two campaigns, which means two audiences.

Facebook’s custom audiences makes this easy, as does LinkedIn’s new-ish Matched Audiences feature. Like with Facebook, you can pick people who’ve visited certain pages on your site, belong to specific lists in your CRM, or whose email address is on a custom .CSV file:

If both of these leads fall off after a few weeks and fail to follow up, you can go back to the beginning to re-engage them. You can use content-based ads all over again to hit back at the primary pain points behind the product or service that you sell.

This seems like a lot of detailed work — largely because it is. But it’s worth it because of scale. You can set these campaigns up, once, and then simply monitor or tweak performance as you go. That means technology is largely running each individual campaign. You don’t need as many people internally to manage each hands-on.

And best of all, it forces you to create a logical system. You’re taking people through a step-by-step process, one tiny commitment at a time, until they seamlessly move from stranger into customer.

Conclusion

Sending out a few tweets won’t make an impact at the end of the day. There’s more competition (read: noise) than ever before, while organic reach has never been lower. The trick isn’t to follow some faux influencer who talks the loudest, but rather the practitioners who are doing it day-in, day-out, with the KPIs to prove it.

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Posted by PolemicToday we’re tackling a question that many of us have asked over the years: how do you increase your chances of getting your content into Google News? We’re delighted to welcome renowned SEO specialist Barry Adams to share the framework… Continue reading →

Posted by willcritchlow

Much has been written and spoken about the interplay of SEO and CRO, and there are a lot of reasons why, in theory, both ought to be working towards a shared goal. Whether it’s simple pragmatism of the business benefit of increasing total number of conversions, or higher-minded pursuits such as the ideal of Google seeking to reward the best user experiences, we have many things that should bring us together.

In practice, though, it’s rarely that simple or that unified. How much effort do the practitioners of each put in to ensure that they are working towards the true shared common goal of the greatest number of conversions?

In asking around, I’ve found that many SEOs do worry about their changes hurting conversion rates, but few actively mitigate that risk. Interestingly, my conversations with CRO experts show that they also often worry about SEOs’ work impacting negatively on conversion rates.

Neither side weights as highly the risks that conversion-oriented changes could hurt organic search performance, but our experiences show that both are real risks.

So how should we mitigate these risks? How should we work together?

But first, some evidence

There are certainly some SEO-centric changes that have a very low risk of having a negative impact on conversion rates for visitors from other channels. If you think about changing meta information, for example, much of that is invisible to users on the page—- maybe that is pure SEO:

And then on the flip side, there are clearly CRO changes that don’t have any impact on your organic search performance. Anything you do on non-indexed pages, for example, can’t change your rankings. Think about work done within a checkout process or within a login area. Google simply isn’t seeing those changes:

But everything else has a potential impact on both, and our experience has been showing us that the theoretical risk is absolutely real. We have definitely seen SEO changes that have changed conversion rates, and have experience of major CRO-centered changes that have had dramatic impacts on search performance (but more on that later). The point is, there’s a ton of stuff in the intersection of both SEO and CRO:

So throughout this post, I’ve talked about our experiences, and work we have done that has shown various impacts in different directions, from conversion rate-centric changes that change search performance and vice versa. How are we seeing all this?

Well, testing has been a central part of conversion rate work essentially since the field began, and we’ve been doing a lot of work in recent years on SEO A/B testing as well. At our recent London conference, we announced that we have been building out new features in our testing platform to enable what we are calling full funnel testing which looks simultaneously at the impact of a single change on conversion rates, and on search performance:

If you’re interested in the technical details of how we do the testing, you can read more about the setup of a full funnel test here. (Thanks to my colleagues Craig Bradford and Tom Anthony for concepts and diagrams that appear throughout this post).

But what I really want to talk about today is the mixed objectives of CRO and SEO, and what happens if you fail to look closely at the impact of both together. First: some pure CRO.

An example CRO scenario: The business impact of conversion rate testing

In the example that follows, we look at the impact on an example business of a series of conversion rate tests conducted throughout a year, and see the revenue uplift we might expect as a result of rolling out winning tests, and turning off null and negative ones. We compare the revenue we might achieve with the revenue we would have expected without testing. The example is a little simplified but it serves to prove our point.

We start on a high with a winning test in our first month:

After starting on a high, our example continues through a bad strong — a null test (no confident result in either direction) followed by three losers. We turn off each of these four so none of them have an actual impact on future months’ revenue:

Let’s continue something similar out through the end of the year. Over the course of this example year, we see 3 months with winning tests, and of course we only roll out those ones that come with uplifts:

By the end of this year, even though more tests have failed than have succeeded, you have proved some serious value to this small business, and have moved monthly revenue up significantly, taking annual revenue for the year up to over £1.1m (from a £900k starting point):

Is this the full picture, though?

What happens when we add in the impact on organic search performance of these changes we are rolling out, though? Well, let’s look at the same example financials with a couple more lines showing the SEO impact. That first positive CRO test? Negative for search performance:

If you weren’t testing the SEO impact, and only focused on the conversion uplift, you’d have rolled this one out. Carrying on, we see that the next (null) conversion rate test should have been rolled out because it was a win for search performance:

Continuing on through the rest of the year, we see that the actual picture (if we make decisions of whether or not to roll out changes based on the CRO testing) looks like this when we add in all the impacts:

So you remember how we thought we had turned an expected £900k of revenue into over £1.1m? Well, it turns out we’ve added less than £18k in reality and the revenue chart looks like the red line:

Let’s make some more sensible decisions, considering the SEO impact

Back to the beginning of the year once more, but this time, imagine that we actually tested both the conversion rate and search performance impact and rolled out our tests when they were net winners. This time we see that while a conversion-focused team would have rolled out the first test:

We would not:

Conversely, we would have rolled out the second test because it was a net positive even though the pure CRO view had it neutral / inconclusive:

When we zoom out on that approach to the full year, we see a very different picture to either of the previous views. By rolling out only the changes that are net positive considering their impact on search and conversion rate, we avoid some significant drops in performance, and get the chance to roll out a couple of additional uplifts that would have been missed by conversion rate changes alone:

The upshot being a +45% uplift for the year, ending the year with monthly revenue up 73%, avoiding the false hope of the pure conversion-centric view, and real business impact:

Now of course these are simplified examples, and in the real world we would need to look at impacts per channel and might consider rolling out tests that appeared not to be negative rather than waiting for statistical significance as positive. I asked CRO expert Stephen Pavlovich from conversion.com for his view on this and he said:

Most of the time, we want to see if making a change will improve performance. If we change our product page layout, will the order conversion rate increase? If we show more relevant product recommendations, will the Average Order Value go up?

But it’s also possible that we will run an AB test not to improve performance, but instead to minimize risk. Before we launch our website redesign, will it lower the order conversion rate? Before we put our prices up, what will the impact be on sales?

In either case, there may be a desire to deploy the new variation — even if the AB test wasn’t significant.

If the business supports the website redesign, it can still be launched even without a significant impact on orders — it may have had significant financial and emotional investment from the business, be a better fit for the brand, or get better traction with partners (even if it doesn’t move the needle in on-site conversion rate). Likewise, if the price increase didn’t have a positive/negative effect on sales, it can still be launched.

Most importantly, we wouldn’t just throw away a winning SEO test that reduced conversion rate or a winning conversion rate test that negatively impacted search performance. Both of these tests would have come from underlying hypotheses, and by reaching significance, would have taught us something. We would take that knowledge and take it back as input into the next test in order to try to capture the good part without the associated downside.

All of those details, though, don’t change the underlying calculus that this is an important process, and one that I believe we are going to need to do more and more.

The future for effective, accountable SEO

There are two big reasons that I believe that the kind of approach I have outlined above is going to be increasingly important for the future of effective, accountable SEO:

1. We’re going to need to do more testing generally

I talked in a recent Whiteboard Friday about the surprising results we are seeing from testing, and the increasing need to test against the Google black box:

I don’t see this trend reversing any time soon. The more ML there is in the algorithm, and the more non-linear it all becomes, the less effective best practices will be, and the more common it will be to see surprising effects. My colleague Dom Woodman talked about this at our recent SearchLove London conference in his talk A Year of SEO Split Testing Changed How I Thought SEO Worked:

2. User signals are going to grow in importance

The trend towards Google using more and more real and implied user satisfaction and task completion metrics means that conversion-centric tests and hypotheses are going to have an increasing impact on search performance (if you haven’t yet read this fascinating CNBC article that goes behind the scenes on the search quality process at Google, I highly recommend it). Hopefully there will be an additional opportunity in the fact that theoretically the winning tests will sync up more and more — what’s good for users will actually be what’s good for search — but the methodology I’ve outlined above is the only way I can come up with to tell for sure.

I love talking about all of this, so if you have any questions, feel free to drop into the comments.

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Posted by MiriamEllis

Let’s go back in time 20 years so I can ask you the question, “How often do you look at a paper map every month?”

Unless you were a cartographer or a frequent traveler, chances are good that your answer would be, “Hmm, maybe less than once a month. Maybe once or twice a year.”

But in 2019, I’d wager there’s scarcely a day that goes by without you using Google Maps when planning to eat out, find a service provider, or find something fun to do. That web-based map in your hand has become a given.

And yet, there’s one thing you’re still not using the Internet for. And it’s something you likely wonder about almost daily. It starts with the question,

“I wonder who around here carries X?”

A real-world anecdote

After the tragic fires we’ve had this year in California, I wanted to wet mop all the floors in my house instead of vacuuming them, due to my concerns about particulate pollution in the air. My mother recommended I buy a Swiffer. I needed to know where I could find one locally, but I didn’t turn to the Internet for this, because the Internet doesn’t tell me this. Or at least, it hasn’t done so until now. Few, if any, of the local hardware stores, pharmacies, or big box retailers have reliable, live online inventory. At the same time, calling these places is often a huge hassle because staff isn’t always sure what’s in stock.

And so I ended up going to 3 different shops in search of this particular product. It wasn’t a convenient experience, and it was an all-too-common one.

The next big thing in local already exists

My real-world anecdote about a wet mop is exactly why I’m so pleased to be interviewing Mark Cummins, CEO of Pointy. 90% of purchases still take place in physical stores and it’s Mark who has seen this gap in available online knowledge about offline inventory and has now set out to bridge it.

I predict that within a few years, you’ll be using the Internet to find local inventory as frequently and easily as you’ve come to use its mapping capabilities. This chat with Mark explains why.

The real-world roots of an existing local need

Miriam: Mark, I understand that you were formerly a Google Search Team member, with a background in machine learning, but that your journey with Pointy began by walking into retail shops and talking face-to-face with owners. What did these owners tell you about their challenges in relation to offline/online inventory? A memorable real-world anecdote would be great here.

Mark: I started thinking about this problem because of an experience just like your story about trying to find a Swiffer. I’d recently moved to a new country and I had to buy lots of things to set up a new apartment, so I had that kind of experience all the time. It felt like there was a huge gap there that search engines could help with, but they weren’t.

I had been working at Google developing what became Google Lens (Google’s image recognition search feature). It felt strange that Google could do something so advanced, yet couldn’t answer very basic questions about where to buy things locally.

So I started thinking about ways to fix that. Initially I would just walk into retailers and talk to them about how they managed their inventory. I was trying to figure out if there was some uniform way to bring the inventory information online. I quickly learned that it was going to be hard. Almost every retailer I spoke to had a different method of tracking it. Some kept records on paper. Some didn’t count their inventory at all.

My first idea was a little crazy — I wanted to build a robot for retailers that would drive around the store every night and photograph all the shelves, and use image recognition to figure out the inventory and the prices. I spent some time seriously thinking about that, but then landed on the idea of the Pointy box, which is a much simpler solution.

Miriam: Can you briefly describe what a typical Point of Sale system is like for retailers these days, in light of this being technology most retailers already have in place?

Mark: Well, I would almost say that there isn’t a typical Point of Sale system. The market is really fragmented, it sometimes feels like no two retailers have the same system. There’s a huge range, from the old-style systems that are essentially a glorified calculator with a cash drawer, up to modern cloud-connected systems like Clover, Square, or Lightspeed. It’s very disruptive for retailers to change their POS system, so older systems tend to stay in use for a long time. The systems also differ by vertical — there are specialized systems for pharmacies, liquor stores, etc. Dealing with all of that variation is what makes it so hard to get uniform local inventory data.

A simple inventory solution is born

Miriam: So, you spoke with retailers, listened to their challenges and saw that they already have Point of Sale systems in place. And Pointy was born! Please, describe exactly what a Pointy device is, how it solves the problems you learned about, and fits right in with existing Point of Sales technology.

Mark: Right! It was pretty clear that we needed to find a solution that worked with retailers’ existing systems. So we developed the Pointy box. The Pointy box is a small device that attaches to a retailer’s barcode scanner. Basically it links the barcode scanner to a website we create for the retailer. Whenever the retailer scans a product with their barcode scanner, we recognize the barcode, and list the product on the website. The end result is live website listing everything in the store — here’s an example for Talbot’s Toyland, a toy store in San Mateo. They have over ten thousand products listed on their site, without any manual work.

The experience is pretty much seamless — just plug in Pointy, and watch your store website build itself. The Pointy box connects directly via the cell phone network, so there’s really nothing to set up. Just plug it in and it starts working. New products automatically get added to your store page, old products get removed when you no longer sell them, item stock status syncs automatically. We did quite a bit of machine learning to make that all automatic. Once the site is live, we also have some SEO and SEM tools to help retailers drive search traffic for the products they sell.

Miriam: My understanding is that the Pointy Team had to do a ton of legwork to put together various product catalogues from which data is pulled each time a product is scanned so that its information can be displayed on the web. I’m not familiar with this concept of product catalogues. What are they, what types of information do they contain, and what did you have to do to pull all of this together? Also, is it true that your team hand-reviews all the product data?

Mark: If you’re working in shopping search, then product catalogs are really important. Every mass-market product has a unique barcode number, but unfortunately there’s no master database where you can enter a barcode number and get back the product’s name, image, etc. So basically every retailer has to solve this problem for themselves, laboriously entering the product details into their systems. Pointy helps eliminate that work for retailers.

There are some product catalogs you can license, but each one only covers a fraction of products, and errors are common. We built a big data pipeline to pull together all of this product data into a single catalog and clean it up. We automate a lot of the work, but if you want the highest quality then machine learning alone isn’t enough. So every single product we display also gets approved by a human reviewer, to make sure it’s accurate. We’ve processed millions of products like this. The end result for the retailer is that they just plug in a Pointy box, scan a product, and their website starts populating itself, no data entry required. It’s a pretty magical feeling the first time you see it. Especially if you’ve spent countless hours of your life doing it the old way!

Where real-time local inventory appears on the web

Miriam: So, then, the products the retailer scans create the brand’s own inventory catalogue, which appears on their Pointy page. What tips would you offer to business owners to best integrate their Pointy page with their brand website? Linking to it from the main menu of the website? Something else? And do these Pointy pages feature SEO basics? Please describe.

Mark: Some retailers use Pointy as their main website. Others have it as an additional profile, in the same way that they might have a Facebook page or a Yelp page. The main thing Pointy brings is the full live inventory of the store, which generally isn’t listed anywhere else. To integrate with their other web presences, most just link across from their main sites or social media profiles. A few also embed Pointy into their sites via an iframe.

We work a lot on making these pages as SEO-friendly as possible. The queries we focus on ranking for are things like “product name near me” or “product name, location.” For example, a query like “rubber piggy bank san mateo” currently has the Pointy page for Talbot’s Toyland in #1 position. We have an engineering team working on this all the time, and we’ve actually discovered a few interesting things.

Miriam: And how does this work when, for example, a product goes out of stock or goes on sale for a different price?

Mark: We keep that information updated live. The stock status is updated based on the information from the Pointy box. We also handle price data, though it depends on what features the retailers is using. Some retailers prefer not to display their prices online.

See What’s In Store: Google totally sees the opportunity

Miriam: I was fascinated to learn that Pointy is the launch partner for Google’s See What’s In Store feature, and readers can see an example of this with Talbot’s Toyland. Can you explain what’s involved for retailers who want their inventory to appear in the SWIS area of the Google Business Profile (aka “Knowledge Panel”) and why this represents such an important opportunity? Also, does the business have to pay a commission to Google for inclusion/impressions/clicks?

Mark: This is a pretty exciting feature. It lets retailers display their full product catalogue and live inventory information in the Business Profile on the Google search page. It’s also visible from Google Maps. I’m guessing Google will probably start to surface the information in more ways over time.

It’s completely free for retailers, which is pretty interesting. Google Shopping has always been a paid service, so it’s notable that Google is now offering some organic exposure with this new feature.

I think that this is going to become table stakes for retailers in the next year or two, in the same way that having your opening hours online is now. Consumers are simply going to expect the convenience of finding local product information online. I think that’s a good thing, because it will help local businesses win back customers that might otherwise have gone to Amazon.

We’ve worked a lot with Google to make the setup experience for local retailers very simple. You just link your Pointy account to Google, and your live inventory appears in the Google Business Profile. Behind the scenes we do a lot of technical work to make that happen (including creating Merchant Center accounts, setting up feeds, etc). But the user experience is just a few clicks. We’ve seen a lot of uptake from Pointy users, it’s been a very popular feature. We have a bit more detail on it here.

What about special retail scenarios?

Miriam: So, basically, Pointy makes getting real-world inventory online for small and independent retailers who just don’t have the time to deal with a complicated e-commerce system. I understand that you have some different approaches to offer larger enterprises, involving their existing IT systems. Can you talk a bit about that, please?

Mark: Yes, some larger retailers may be able to send us a direct feed from their inventory systems, rather than installing Pointy boxes at every POS location. We aim to support whatever is easiest for the retailer. We are also directly integrated into modern cloud POS systems like Clover, Square, Lightspeed, Vend, and others. Users of those systems can download a free Pointy app from their system’s app store and integrate with us that way. And for retailers not using those systems, they can use a Pointy box.

Miriam: And what about retailers whose products lack labels/barcodes? Let’s say, a farm stand with constantly-changing seasonal produce, or a clothing boutique with hand-knit sweaters? Is there a Pointy solution for them?

Mark: Unfortunately we’re not a great fit for those kind of retailers. We designed the experience for retailers who sell barcoded products.

Miriam: You’re a former Google staffer, Mark. In local search, Google has become aggressive in taking a cut of an increasing number of local consumer actions and this is particularly hard on small businesses. We’ve got Local Service Ads, paid ads in local packs, booking buttons, etc, all of which struggling independent businesses are having to pay Google for. Right now, these retailers are eager for a competitive edge. How can they differentiate themselves? Please, share tips.

Mark: It’s true, lots of channels that used to be purely organic now have a mix of organic and paid. I think ultimately the paid ads still have to be ROI-positive or nobody will use them, but it’s definitely no fun to pay for traffic you used to get for free.

On the positive side, there are still plenty of openings to reach customers organically. If small businesses invest in staying ahead of the game, they can do very well. Lots of local product searches essentially have no answer, because most retailers haven’t been able to get their inventory online yet. It’s easy to rank well for a query when you’re the only one with the answer. There’s definitely still an opening there for early adopters.

“Pointing” the way to the future

Miriam: Finally, Pointy has only been available in the US since 2016, and in that short amount of time, you’re already serving 1% of the country’s retailers. Congratulations! What does the near future look like to you for retailers and for Pointy? What do you see as Pointy’s mission?

Mark: We want to bring the world’s brick-and-mortar retailers online and give them the tools they need to thrive. More than 90% of retail goes through brick and mortar stores, so there’s no reason they shouldn’t have an amazing technology platform to help them. The fragmentation and difficulty of accessing data has held everyone back, but I think Pointy has a shot at fixing that.

Miriam: Thank you, Mark. I believe Pointy has what it takes to be successful, but I’m going to wish you good luck, anyway!

Summing up

In doing this interview, I learned a ton from Mark and I hope you did, too. If a local retailer you market is seeking a competitive advantage in 2019, I’d seriously be considering early adoption of Google’s See What’s In Store feature. It’s prime Google Business Profile (formerly Knowledge Panel) real estate, and so long as SWIS is free and Pointy is so affordable, there’s a pretty incredible opportunity to set yourself apart in these early days with a very modest investment.

I’m feeling confident about my prediction that we’re on the verge of a new threshold in user behavior, in terms of people using local search to find local inventory. We’ll all have the enjoyment of seeing how this plays out over the next couple of years. And if you heard it first at Moz, that will be extra fun!

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