Monday, November 11, 2019

The Marketing Tactics People Love (And Love to Hate) [Exclusive Survey]

Posted by amandamilligan

I’ve always considered the most challenging part about digital marketing to be prioritizing.

There are hundreds of tactics available to you, and it can be overwhelming to determine which of them are most appropriate for your marketing goals and your target audience. (And we all know what happens when you try to do too much — you do it all poorly.)

It’s critical to analyze the attitudes and behaviors of your current and potential clients/customers in order to best communicate with them in the methods they prefer.

But every now and then, it’s also helpful to zoom out and see how different marketing tactics are faring in general.

That’s why we surveyed 500+ Americans, asking them their thoughts on a variety of inbound and outbound marketing tactics.

Our objective was to better understand which tactics might be most effective on a broad scale and how people might feel about the various tactics they encounter.

Here are the biggest insights.

1. Very few channels "die"

Here’s the thing: The marketing industry experiences a constant ebb and flow. A tactic like email marketing becomes popular, everyone does it, the space becomes diluted, and then other tactics start to gain traction as people seek out “quieter” channels.

That doesn’t mean those tactics no longer work. It just means it becomes harder for your message to be seen because the volume of content out there for people to read is expansive. You have to work harder for it, have an intimate understanding of the information your audience wants, and test relentlessly.

Fractl surveyed 500+ people and asked them, "What is the most effective way for a company to attract your business?" The top result at 54.33% was "Appearing in search results when I'm looking for something I need or want." The bottom result at 20.71% was "Being promoted or endorsed by an influencer on social media or elsewhere."

The prime example of this revealed in this survey is that when asked what people think is the best way to attract their business, they picked snail mail (53.31%) over email (38.37%).

A couple of years ago, I’d never have thought to consider direct mail over email. It’s costly and people tend to find mail cumbersome, sending a lot of it straight to the trash.

But over time, some have started to feel that way about email. It’s hard to filter out all of the spam, discern between good pitches and bad ones, and just sort through what feels like an endless stream of messages. Direct mail has started to feel more like a novelty. In fact, 28% of our respondents said they’ve never clicked on the “Promotions” Gmail tab.

The takeaway: Don’t let anyone tell you a channel is dead (except for maybe MySpace and other sites that are abandoned.) Take advantage of “quiet” channels but only if it makes sense for your audience. Focus on them, and the appropriate channel for you will become more obvious.

For example, some brands are seeing success endeavoring into the print magazine realm, a “quieter” channel that appeals to their specific audiences. (And how many times have we heard that print is dead?)

2. Don't seem intrusive

Privacy has certainly been a hot topic these days, but we shouldn’t be focusing solely on GDPR and other regulations (that’s where don’t be intrusive comes in). It’s not just about what’s legal — it’s also about what’s off-putting. Unsurprisingly, people don’t like to feel like they’re being oddly approached or “followed” online (or anywhere).

That probably explains why our survey found that of the 78% of people who said they notice retargeted ads, 56% have negative feelings toward them. That’s a pretty large amount of negativity for a tactic. In a separate question, 53% said they have ad blockers, choosing to bypass ads altogether.

Outbound marketing is about reaching out to people cold, but there’s an art to this.

Fractl surveyed 500+ people and asked them if they felt positively, negatively, or neutrally about different marketing tactics. Website and blog articles had the best sentiment. Website ads had the worst sentiment.

Traditional advertising achieves No. 2 on the sentiment scale, and my interpretation of this is that people are so used to seeing advertisements on television and hearing them on the radio that it no longer has an intrusive vibe.

Email, sponsored social media posts, and ads still can carry that feeling, though.

Does that mean you shouldn’t utilize these tactics? Of course not. It does mean you have to be very strategy in applying them, though, or you’ll turn off your audience almost immediately.

The takeaway: When utilizing outbound strategies, make sure the recipients understand why they’re receiving the information and ensure what you’re providing speaks to a want or need of theirs. Make the value you’re providing immediately clear.

For example, I made a reservation at an Italian restaurant called Osteria Morini about a year ago. I received an email from them with the subject line “Fall Pasta Classes are Here!” Even though I didn’t remember signing up for their updates, I opened the email because I knew exactly what they were trying to tell me and I was interested. I also just went back and checked; they’ve only emailed me once since the reservation. That’s an extreme — I don’t advocate you sending one email a year — but only send emails with real value.

3. Prioritize search

It shouldn’t come as a huge surprise that search engine optimization won out as one of the strongest strategies out there.

Notice in the first graph in the article that appearing in search results was listed as the best way to earn respondents’ business, and in the second graph, you’ll see that reading the type of content you’d find on those results carries the best sentiment.

Not only is it effective, but it’s also a common practice.

Fractl surveyed 500+ people and asked them, "In the last week, have you done any of the following?" The top result at 89% was "Used online search to find information about a company or product." The bottom result at 30.4% was "Read a company or brand blog post."

Using search engines to find answers is essentially an inherent online experience; nearly everyone does it, and if you’re not showing up in the SERPs, you can be missing out on massive opportunities to increase your brand awareness, connect with potential clients/customers, and build authority in your space.

I’d say authority is a huge piece of why search is so important to people. When you rank highly, it’s almost like the online equivalent of being published — “people” (other sites and Google) — vouch for you.


Fractl surveyed 500+ people and asked them, "How do you learn about a company or product?" The top result at 86.4% was "Do an online search." The bottom result at 15.8% was "Download content from their site."

The authority piece is greater represented in the graph above. Reading customer reviews comes in right behind performing searches for how people learn more about a company or product, because people are constantly looking for authority and quality indicators in order to make the best decisions possible. (This is why E-A-T has been such a hot topic lately.)

The takeaway: SEO should always be a primary objective of your marketing team. If you’re in a competitive space and finding it difficult to rank for your target keywords, focus on the long-tail for queries that are directly relevant to your business. That way, you’re building authority with people who are already close to becoming customers/clients.

For example, when searching for daily planners, I noticed there are a few related keywords regarding daily planners that start as early as 5 a.m. The Better Dayplanner has an article that ranks for these types of keywords, meaning that people looking for something very specific will see them first. Sure, the search volume is low, but the traffic is as relevant as you can get.

Conclusion

After reading through this article (and reviewing the full inbound and outbound marketing survey), you can get a sense of which of your tactics may need modifying and which opportunities may be present. There’s no universally right or wrong answer; it’s highly dependent on the specifics of your brand and your target audience. But knowing general trends and preferences can help you shape your strategy so it’s as effective as possible.


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Friday, November 8, 2019

What Is BERT? - Whiteboard Friday

Posted by BritneyMuller

There's a lot of hype and misinformation about the new Google algorithm update. What actually is BERT, how does it work, and why does it matter to our work as SEOs? Join our own machine learning and natural language processing expert Britney Muller as she breaks down exactly what BERT is and what it means for the search industry.

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Video Transcription

Hey, Moz fans. Welcome to another edition of Whiteboard Friday. Today we are talking about all things BERT and I'm super excited to attempt to really break this down for everyone. I don't claim to be a BERT expert. I have just done lots and lots of research. I've been able to interview some experts in the field and my goal is to try to be a catalyst for this information to be a little bit easier to understand. 

There is a ton of commotion going on right now in the industry about you can't optimize for BERT. While that is absolutely true, you cannot, you just need to be writing really good content for your users, I still think many of us got into this space because we are curious by nature. If you are curious to learn a little bit more about BERT and be able to explain it a little bit better to clients or have better conversations around the context of BERT, then I hope you enjoy this video. If not, and this isn't for you, that's fine too.

Word of caution: Don't over-hype BERT!

I’m so excited to jump right in. The first thing I do want to mention is I was able to sit down with Allyson Ettinger, who is a Natural Language Processing researcher. She is a professor at the University of Chicago. When I got to speak with her, the main takeaway was that it's very, very important to not over-hype BERT. There is a lot of commotion going on right now, but it's still far away from understanding language and context in the same way that we humans can understand it. So I think that's important to keep in mind that we are not overemphasizing what this model can do, but it's still really exciting and it's a pretty monumental moment in NLP and machine learning. Without further ado, let's jump right in.

Where did BERT come from?

I wanted to give everyone a wider context to where BERT came from and where it's going. I think a lot of times these announcements are kind of bombs dropped on the industry and it's essentially a still frame in a series of a movie and we don't get the full before and after movie bits. We just get this one still frame. So we get this BERT announcement, but let's go back in time a little bit. 

Natural language processing

Traditionally computers have had an impossible time understanding language. They can store text, we can enter text, but understanding language has always been incredibly difficult for computers. So along comes natural language processing (NLP), the field in which researchers were developing specific models to solve for various types of language understanding. A couple of examples are named entity recognition, classification. We see sentiment, question answering. All of these things have traditionally been sold by individual NLP models and so it looks a little bit like your kitchen. 

If you think about the individual models like utensils that you use in your kitchen, they all have a very specific task that they do very well. But when along came BERT, it was sort of the be-all end-all of kitchen utensils. It was the one kitchen utensil that does ten-plus or eleven natural language processing solutions really, really well after it's fine tuned. This is a really exciting differentiation in the space. That's why people got really excited about it, because no longer do they have all these one-off things. They can use BERT to solve for all of this stuff, which makes sense in that Google would incorporate it into their algorithm. Super, super exciting. 

Where is BERT going?

Where is this heading? Where is this going? Allyson had said, 

"I think we'll be heading on the same trajectory for a while building bigger and better variants of BERT that are stronger in the ways that BERT is strong and probably with the same fundamental limitations."

There are already tons of different versions of BERT out there and we are going to continue to see more and more of that. It will be interesting to see where this space is heading.

How did BERT get so smart?

How about we take a look at a very oversimplified view of how BERT got so smart? I find this stuff fascinating. It is quite amazing that Google was able to do this. Google took Wikipedia text and a lot of money for computational power TPUs in which they put together in a V3 pod, so huge computer system that can power these models. And they used an unsupervised neural network. What's interesting about how it learns and how it gets smarter is it takes any arbitrary length of text, which is good because language is quite arbitrary in the way that we speak, in the length of texts, and it transcribes it into a vector.

It will take a length of text and code it into a vector, which is a fixed string of numbers to help sort of translate it to the machine. This happens in a really wild and dimensional space that we can't even really imagine. But what it does is it puts context and different things within our language in the same areas together. Similar to Word2vec, it uses this trick called masking


So it will take different sentences that it's training on and it will mask a word. It uses this bi-directional model to look at the words before and after it to predict what the masked word is. It does this over and over and over again until it's extremely powerful. And then it can further be fine-tuned to do all of these natural language processing tasks. Really, really exciting and a fun time to be in this space.

In a nutshell, BERT is the first deeply bi-directional. All that means is it's just looking at the words before and after entities and context, unsupervised language representation, pre-trained on Wikipedia. So it's this really beautiful pre-trained model that can be used in all sorts of ways. 

What are some things BERT cannot do? 

Allyson Ettinger wrote this really great research paper called What BERT Can't Do. There is a Bitly link that you can use to go directly to that. The most surprising takeaway from her research was this area of negation diagnostics, meaning that BERT isn't very good at understanding negation


For example, when inputted with a Robin is a… It predicted bird, which is right, that's great. But when entered a Robin is not a… It also predicted bird. So in cases where BERT hasn't seen negation examples or context, it will still have a hard time understanding that. There are a ton more really interesting takeaways. I highly suggest you check that out, really good stuff.

How do you optimize for BERT? (You can't!)

Finally, how do you optimize for BERT? Again, you can't. The only way to improve your website with this update is to write really great content for your users and fulfill the intent that they are seeking. And so you can't, but one thing I just have to mention because I honestly cannot get this out of my head, is there is a YouTube video where Jeff Dean, we will link to it, it's a keynote by Jeff Dean where he speaking about BERT and he goes into natural questions and natural question understanding. The big takeaway for me was this example around, okay, let's say someone asked the question, can you make and receive calls in airplane mode? The block of text in which Google's natural language translation layer is trying to understand all this text. It's a ton of words. It's kind of very technical, hard to understand.

With these layers, leveraging things like BERT, they were able to just answer no out of all of this very complex, long, confusing language. It's really, really powerful in our space. Consider things like featured snippets; consider things like just general SERP features. I mean, this can start to have a huge impact in our space. So I think it's important to sort of have a pulse on where it's all heading and what's going on in this field. 

I really hope you enjoyed this version of Whiteboard Friday. Please let me know if you have any questions or comments down below and I look forward to seeing you all again next time. Thanks so much.

Video transcription by Speechpad.com


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Finding Ideas for a Video Series or Podcast - Whiteboard Friday

Posted by PhilNottingham

Video and podcasts are only growing in popularity, proving to be an engaging way to reach your audience and find ways to talk about your industry or product. But it's a crowded market out there, and finding a good idea is only half the battle. Join video marketing extraordinaire Phil Nottingham from Wistia as he explores how we can both uncover great ideas for a podcast or video series and follow through on them in this week's episode of Whiteboard Friday.

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Video Transcription

Howdy, Moz fans. My name is Phil Nottingham, and welcome to another edition of Whiteboard Friday. Today we're going to talk about how to come up with a great idea for your video series or podcast. I think a lot of businesses out there understand that there's just this great opportunity now to do a longer form series, a show in podcast or video form, but really struggle with that moment of finding what kind of idea could take them to the next level and help them stand out.

1. Audience

I think the most common error that businesses make is to start with the worst idea in the world, which is interviewing our customers about how they use our product. I'm sure many of you have accidentally fallen down this trap, where you've thought, "Ah, maybe that will be a good idea." But the thing is even if you're Ferrari or Christian Louboutin or the most desirable product in the world, it's never going to be interesting for someone to sit there and just listen to your customers talking about your product.

The problem is that your customers are not a unique group of people, aside from the fact that they use your product. Usually there isn't anything else that brings them together. For this kind of content, for a video series and podcast to really stand out and to grow in terms of their audience, we need to harness word of mouth. Word of mouth doesn't grow through the way we often think about audience growth in marketing.

Many of us, particularly in the performance marketing space, are used to thinking about funnels. So we get more and more traffic into the funnel, get more people in there, and ultimately some of them convert. But the way word of mouth works is that a small group of people start communicating to another group of people who start communicating to another group of people. You have these ever-expanding circles of communication that ultimately allow you to grow your audience.

How to find a niche audience

But that means you need to start with a group of people who are talking to one another. Invariably, your customers are not talking to each other as a kind of rule of thumb. So what you need to do is find a group of people, an audience who are talking to each other, and that really means a subculture, a community, or maybe an interest group. So find your group of customers and work out what is a subset of customers, what kind of community, wider culture they're part of, a group of people who you could actually speak to.

The way you might find this is using things like Reddit. If there's a subculture, there's going to be a subreddit. A tool like SparkToro will allow you to discover other topics that your customer base might be interested in. Slack communities can be a great source of this. Blogs, there's often any sort of topic or a niche audience have a blog. Hashtags as well on social media and perhaps meetup groups as well.

So spend some time finding who this audience is for your show, a real group of people who are communicating with one another and who ultimately are someone who you could speak to in a meaningful way. 

2. Insight

Once you've got your audience, you then need to think about the insight. What the insight is, is this gap between desire and outcome. So what you normally find is that when you're speaking to groups of people, they will have something they want to achieve, but there is a barrier in the way of them doing it.

This might be something to do with tools or hardware/software. It could be just to do with professional experience. It could be to do with emotional problems. It could be anything really. So you need to kind of discover what that might be. The essential way to do that is just through good, old-fashioned talking to people. 

  • Focus groups, 
  • Surveys, 
  • Social media interactions, 
  • Conversations, 
  • Data that you have from search, like using Google Search Console, 
  • Internal site search, 
  • Search volume 

That kind of thing might tell you exactly what sort of topics, what problems people are having that they really try to solve in this interest group.

Solve for the barrier

So what we need to do is find this particular little nugget of wisdom, this gold that's going to give us the insight that allows us to come up with a really good idea to try and solve this barrier, whatever that might be, that makes a difference between desire and outcome for this audience. Once we've got that, you might see a show idea starting to emerge. So let's take a couple of examples.

A few examples

Let's assume that we are working for like a DIY supplies company. Maybe we're doing just sort of piping. We will discover that a subset of our customers are plumbers, and there's a community there of plumbing professionals. Now what might we find about plumbers? Well, maybe it's true that all plumbers are kind of really into cars, and one of the challenges they have is making sure that their car or their van is up to the job for their work.

Okay, so we now have an interesting insight there, that there's something to do with improving cars that we could hook up for plumbers. Or let's say we are doing a furniture company and we're creating furniture for people. We might discover that a subset of our audience are actually amateur carpenters who really love wooden furniture. Their desire is to become professional.

But maybe the barrier is they don't have the skills or the experience or the belief that they could actually do that with their lives and their career. So we see these sort of very personal problems that we can start to emerge an idea for a show that we might have. 

3. Format

So once we've got that, we can then take inspiration from existing TV and media. I think the mistake that a lot of us make is thinking about the format that we might be doing with a show in a very broad sense.

Don't think about the format in a broad sense — get specific

So like we're doing an interview show. We're doing a talk show. We're doing a documentary. We're doing a talent show. Whatever it might be. But actually, if we think about the great history of TV and radio the last hundred years or so, all these really smart formats have emerged. So within talk show, there's "Inside the Actors Studio," a very sort of serious, long, in-depth interview with one person about their practice.

There's "The Tonight Show Starring Jimmy Fallon," which has got lots of kind of set pieces and sketches and things that intermingle with the interview. There's "Ellen," where multiple people are interviewed in one show. If we think about documentaries, there's like fly-on-the-wall stuff, just run and gun with a camera, like "Diners, Drive-Ins and Dives." Carrying on the food thing, there's "Chef's Table," where it's very planned and meticulously shot and is an exposé of one particular chef.

Or something like "Ugly Delicious," which is a bit more like a kind of exploratory piece of documentary, where there's kind of one protagonist going around the world and they piece it together at the end. So you can think about all these different formats and try to find an idea that maybe has been done before in TV in some format and find your way through that. 

A few more examples

So let's think about our plumber example. Plumbers who love cars, well, we could do "Pimp My Ride for Tradesmen."

That's an interesting idea for a talk. Or let's say we're going after like amateur carpenters who would love to be professional. We could easily do "American Idol for Lumberjacks or Carpenters." So we can start to see this idea emerge. Or let's take a kind of B2B example. Maybe we are a marketing agency, as I'm sure many of you are. If you're a marketing agency, maybe you know that some of your customers are in startups, and there's this startup community.

One of the real problems that startups have is getting their product ready for market. So you could kind of think, well, the barrier is getting the product ready for market. We could then do "Queer Eye for Product Teams and Startups,"and we'll bring in five specialists in different areas to kind of get their product ready and sort of iron out the details and make sure they're ready to go to market and support marketing.

So you can start to see by having a clear niche audience and an insight into the problems that they're having, then pulling together a whole list of different show ideas how you can bring together an idea for a potential, interesting TV show, video series, or podcast that could really make your business stand out. But remember that great ideas are kind of 10 a penny, and the really hard thing is finding the right one and making sure that it works for you.

So spend a lot of time coming up with lots and lots of different executions, trying them out, doing kind of little pilots before you work out and commit to the idea that works for you. The most important thing is to keep going and keep trying and teasing out those ideas rather than just settling on the first thing that comes to mind, because usually it's not going to be the right answer. So I hope that was very useful, and we will see you again on another episode of Whiteboard Friday.

Take care.

Video transcription by Speechpad.com


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Tuesday, November 5, 2019

This Is What Happens When You Accidentally De-Index Your Site from Google

Posted by Jeff_Baker

Does reading that title give you a mini-panic attack?

Having gone through exactly as the title suggests, I can guarantee your anxiety is fully warranted.

If you care to relive my nightmare with me — perhaps as equal parts catharsis and SEO study — we will walk through the events chronologically.

Are you ready?

August 4th, 2019

It was a Sunday morning. I was drinking my coffee and screwing around in our SEO tools, like normal, not expecting a damned thing. Then … BAM!

What. The. Hell?

As SEOs, we’re all used to seeing natural fluctuations in rankings. Fluctuations, not disappearances.

Step 1: Denial

Immediately my mind goes to one place: it’s a mistake. So I jumped into some other tools to confirm whether or not Ahrefs was losing its mind.

Google Analytics also showed a corresponding drop in traffic, confirming something was definitely up. So as an SEO, I naturally assumed the worst…

Step 2: Algo panic

Algorithm update. Please, please don’t let it be an algo update.

I jumped into Barracuda’s Panguin Tool to see if our issue coincided with a confirmed update.

No updates. Phew.

Step 3: Diagnosis

Nobody ever thinks clearly when their reptile brain is engaged. You panic, you think irrationally and you make poor decisions. Zero chill.

I finally gathered some presence of mind to think clearly about what happened: It’s highly unusual for keywords rankings to disappear completely. It must be technical.

It must be indexing.

A quick Google search for the pages that lost keyword rankings confirmed that the pages had, in fact, disappeared. Search Console reported the same:

Notice the warning at the bottom:

No: ‘noindex’ detected in ‘robots’ meta tag

Now we were getting somewhere. Next, it was time to confirm this finding in the source code.

Our pages were marked for de-indexing. But how many pages were actually de-indexed so far?

Step 4: Surveying the damage

All of them. After sending a few frantic notes to our developer, he confirmed that a sprint deployed on Thursday evening (August 1, 2019), almost three days prior, had accidentally pushed the code live on every page.

But was the whole site de-indexed?

It’s highly unlikely, because in order for that to happen, Google would have had to crawl every page of the site within three days in order to find the ‘noindex’ markup. Search Console would be no help in this regard, as its data will always be lagging and may never pick up the changes before they are fixed.

Even looking back now, we see that Search Console only picked up a maximum of 249 affected pages, of over 8,000 indexed. Which is impossible, considering our search presence was cut by one-third an entire week after the incident was fixed.

Note: I will never be certain how many pages were fully de-indexed in Google, but what I do know is that EVERY page had ‘noindex’ markup, and I vaguely remember Googling ‘site:brafton.com’ and seeing roughly one-eighth of our pages indexed. Sure wish I had a screenshot. Sorry.

Step 1: Fix the problem

Once the problem was identified, our developer rolled back the update and pushed the site live as it was before the ‘noindex’ markup. Next came the issue of re-indexing our content.

Step 2: Get the site recrawled ASAP

I deleted the old sitemap, built a new one and re-uploaded to Search Console. I also grabbed most of our core product landing pages and manually requested re-indexing (which I don’t fully believe does anything since the most recent SC update).

Step 3: Wait

There was nothing else we could do at this point, other than wait. There were so many questions:

  • Will the pages rank for the same keywords as they did previously?
  • Will they rank in the same positions?
  • Will Google “penalize” the pages in some way for briefly disappearing?

Only time would tell.

August 8th, 2019 (one week) - 33% drop in search presence

In assessing the damage, I’m going to use the date in which the erroring code was fully deployed and populated on live pages (August 2nd) as ground zero. So the first measurement will be seven days completed, August 2nd through August 8th.

Search Console would likely give me the best indication as to how much our search presence had suffered.

We had lost about 33.2% of our search traffic. Ouch.

Fortunately, this would mark the peak level of damage we experienced throughout the entire ordeal.

August 15th, 2019 (two weeks) - 23% drop in traffic

During this period I was keeping an eye on two things: search traffic and indexed pages. Despite re-submitting my sitemap and manually fetching pages in Search Console, many pages were still not being indexed — even core landing pages. This will become a theme throughout this timeline.

As a result of our remaining unindexed pages, our traffic was still suffering.

Two weeks after the incident and we were still 8% down, and our revenue-generating conversions fell with the traffic (despite increased conversion rates).

August 22nd, 2019 (three weeks) - 13% drop in traffic

Our pages were still indexing slowly. Painfully slowly, while I was watching my commercial targets drop through the floor.

At least it was clear that our search presence was recovering. But how it was recovering was of particular interest to me.

Were all the pages re-indexed, but with decreased search presence?

Were only a portion of the pages re-indexed with fully restored search presence?

To answer this question, I took a look at pages that were de-indexed, and re-indexed, individually. Here is an example of one of those pages:

Here’s an example of a page that was de-indexed for a much shorter period of time:

In every instance I could find, each page was fully restored to its original search presence. So it didn’t seem to be a matter of whether or not pages would recover, it was a matter of when pages would be re-indexed.

Speaking of which, Search Console has a new feature in which it will “validate” erroring pages. I started this process on August 26th. After this point, SC slowly recrawled (I presume) these pages to the tune of about 10 pages per week. Is that even faster than a normally scheduled crawl? Do these tools in SC even do anything?

What I knew for certain was there were a number of pages still de-indexed after three weeks, including commercial landing pages that I counted on to drive traffic. More on that later.

August 29th, 2019 (four weeks) - 9% drop in traffic

At this point I was getting very frustrated, because there were only about 150 pages remaining to be re-indexed, and no matter how many times I inspected and requested a new indexing in Search Console, it wouldn’t work.

These pages were fully capable of being indexed (as reported by SC URL inspection), yet they wouldn’t get crawled. As a result, we were still 9% below baseline, after nearly a month.

One particular page simply refused to be re-indexed. This was a high commercial value product page that I counted on for conversions.

In my attempts to force re-indexing, I tried:

  • URL inspection and requesting indexing (15 times over the month).
  • Updating the publish date, then requesting indexing.
  • Updating the content and publish date, then requesting indexing.
  • Resubmitting sitemaps to SC.

Nothing worked. This page would not re-index. Same story for over one hundred other less commercially impactful URLs.

Note: This page would not re-index until October 1st, two full months after it was de-indexed.

By the way, here’s what our overall recovery progress looked like after four weeks:

September 5th, 2019 (five weeks) - 10.4% drop in traffic

The great plateau. At this point we had reindexed all of our pages, save for the ~150 or so supposedly being “validated.”

They weren’t. And they weren’t being recrawled either.

It seemed that we would likely fully recover, but the timing was in Google’s hands, and there was nothing I could do to impact it.

September 12th, 2019 (six weeks) - 5.3% gain in traffic

It took about six weeks before we fully recovered our traffic.

But in truth, we still hadn’t fully recovered our traffic, in that some content overperformed and was overcompensating for a number of pages that were not yet indexed. Notably, our product page that wouldn’t be indexed for another ~2.5 weeks.

On balance, our search presence recovered after six weeks. But our content wasn’t fully re-indexed until eight-plus weeks after fixing the problem.

Conclusion

For starters, definitely don’t de-index your site on accident, for an experiment, or any other reason. It stings. I estimate that we purged about 12% of all organic traffic amounting to an equally proportionate drop on commercial conversions.

What did we learn??

Once pages re-indexed, they were fully restored in terms of search visibility. The biggest issue was getting them re-indexed.

Some main questions we answered with this accidental experiment:

Did we recover?

Yes, we fully recovered and all URLs seem to drive the same search visibility.

How long did it take?

Search visibility returned to baseline after six weeks. All pages re-indexed after about eight to nine weeks.


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Monday, November 4, 2019

Have Your Agency’s Clients Considered a Local Product Kiosk? Google Has.

Posted by MiriamEllis

File this under fresh ideas for stagnant clients.

It’s 10:45 at night and I’m out of:

  • Tortillas
  • Avocados
  • Salsa

Maybe I just got off of work, like millions of other non-nine-to-fivers. Maybe I was running around with my family all day and didn’t get my errands done. Maybe I was feeling too sick to appear in a public grocery store wrapped in the ratty throw from my sofa.

And now, most of the local shops are closed for the night and I’m sitting here, taco-less and sad.

But what if it didn’t have to be that way? What if I could search Google and find a kiosk just a couple of blocks away that would vend me solutions, no matter what time of night or day?

Something old is becoming new again, just like home delivery. And for your agency’s local business clients, the opportunity could become an amazing competitive advantage.

What’s up with kiosks?

Something old

The automat was invented in Germany in the late 19th century and took off in the US in the decades following, with industry leader Horn & Hardart’s last New York location only closing in 1991. These famous kiosks fed thousands of Americans on a daily basis with on-demand servings of macaroni, fish cakes, baked beans, and chicory coffee. The demise of the automat is largely blamed on the rise of the fast food industry, with Burger Kings even opening doors at former automat locations.

Something new

A couple of weeks ago, I was watching an episode of my favorite local SEO news roundup in which Ignitor Digital’s Carrie Hill mentioned a meat vending kiosk. I was immediately intrigued and wanted to know more about this. What I learned sparked my imagination on behalf of local businesses which are always benefitted by at least considering fresh ideas, even if those ideas are actually just taking a page from history and editing it a bit.

Something inspirational

What I learned from my research is that the Applestone Meat Company is distinguishing itself from the competition by offering a 24/7 butcher shop via two vending installations in the state of New York. They also have a drive-up service window from 11am–6pm, but for the countless potential customers who are at work or elsewhere during so-called “normal business hours,” the meat kiosks are ever-ready to serve.

CEO Joshua Applestone says he was inspired by the memory of Horn & Hardart and he must be one smart local business owner to have taken this bold plunge. The company has already earned some pretty awesome unstructured citations from the likes of Bloomberg with this product marketing strategy and they’re planning to open ten more kiosks in the near future.

But Applestone isn’t alone. A kiosk can technically just be a fancy vending machine. Check out Chicago startup Farmer’s Fridge. They recently closed a $30 million Series C round led by one-time Google CEO Eric Schmidt’s Innovation Endeavors. Their 200+ midwestern units provide granola, Greek yogurt, pasta, wraps, beverages, and similar on-the-go fare, and they donate leftovers to local food pantries.

Americans have long been accustomed to ATM machines. DVD and game rental stations are old news to us. We are nowhere near Japan, with its sixty-billion-dollar-a-year, national vending machine density of one machine per 23 citizens, and its automated sales of everything from ramen to socks to umbrellas. Geography and economics don’t point to the need to go to such a level in the US, but where convenience is truly absent, opportunity may reside. What might that look like?

Use your imagination

My corner of the world is famous for its sourdough bread. There are hundreds of regional bakeries competing with one another for the crustiest, lightest, most indulgent loaf. But, if you don’t make it to the local stores by early afternoon, your favorite brand is likely to have sold out. And if you’re working the 47-hour American work week, or gigging California night and day but don’t want to live on fast food, you’d likely be quite grateful to have your access to artisan baguettes restored.

Just imagine every bread bakery around the SF Bay Area installing a kiosk outside its front door, and you can hear the satisfied after-hours crunching, can’t you?

Applestone is selling unprepared meat, Farmer’s Fridge is selling prepared meals, and almost anything people nosh could be a candidate for a kiosk, but why should on-demand products be limited to food? I let my imagination meander and jotted down a quick list of things people might buy at various off-hours, if a machine existed outside the storefront:

  • Books/magazines
  • Weather-appropriate basic apparel (sweatshirts, socks, t-shirts)
  • First aid supplies
  • Baby care supplies
  • Emergency electronics (chargers, batteries, flashlights)
  • Basic auto repair supplies (headlight bulbs, wipers, puncture kits)
  • Personal care products (bathroom tissue, toiletries)
  • Office supplies (printer ink, paper, envelopes, stamps)
  • Household goods (lightbulbs, laundry soap, pantry basics)
  • Pet supplies
  • Travel/camping/athletic supplies
  • Basic craft supplies, small games, gifts, etc.

What if customers who do their morning bike ride at 5 AM knew they could stop by your client’s kiosk to fix a punctured tire? What if night workers knew they could pick up a box of light bulbs or bandages or cat food on their way to their shift? Think of the convenience — in some instances even life-saving help — that could be provided to travelers on the road at all hours, members of your community who are housing-insecure, or whole neighborhoods that lack access to basic goods?

Not every local business has the right model for a kiosk, but once I started to think about it, I realized just how many of them could. I’m initially envisioning these machines being installed at the place of business, but, where the scenario is right, a company with the right type of inventory could certainly place additional kiosks in strategic locations around the communities they wish to serve.

Kiosk Local SEO

Clearly, kiosks can generate revenue, but what could they do for clients’ online presence? The guidelines for representing your business on Google already support the creation of local business listings for ATMs, video rental stations, and express mail dropboxes. But I went straight to Google with the Applewood example to ask if this emerging type of kiosk would be permitted to create listings. They were kind enough to reply:

Twitter DM from Google rep: kiosks are able to create listings, as per guidelines

The link in the Twitter DM reply just pointed to the general guidelines, and I can find no reference to the term “Food Kiosk listing” in them. It’s the first time I’ve ever heard this terminology. But, clearly this representative is naming food kiosks as a “thing.” Google, it seems, is already quite aware of this business model. And the proof of their support is in the Maps pudding:

My, my! Talk about having the ability to hyperlocalize your local search marketing to fit Google’s extreme emphasis on user-to-business proximity. Enough to make any local SEO agency see conversions and dollar signs for clients.

Tip #1: Helpline phone numbers

I’ve written about ATM SEO in the past for financial publications, and so I’ll add one important tip for creating eligible Google listings for kiosks: guidelines require that you have a helpline phone number for kiosk users. I would post this number both on the listings and on the units, themselves. Note that this will likely mean you have a shared phone number on multiple listings, which isn’t typically deemed ideal for local search marketing, but if kiosks become your model and you avoid any semblance of creating fake listings, Google can likely handle it.

Tip #2: Unique local landing pages for your kiosks

I can also see value in creating unique location landing pages on client websites for their kiosks, especially if they aren’t stationed at your physical location. These pages could give excellent driving and walking directions for each unit, explain how to use the machine, feature reviews and testimonials for that location, and perhaps highlight new inventory.

Tip #3: Capitalize on your social media

Social media will also be an excellent vehicle for letting particular neighborhoods know about client kiosks and engaging with communities to understand their sentiments. Seek abundant feedback about what is and isn’t working for customers and how inventory could better serve their needs. And, of course, be sure every client is monitoring reviews like a low-flying hawk.

Is there an appetite for kiosks?

Image credit: Ben Chun

I’m a longtime observer of rural local SEO. I’ve learned that being intentional in noticing small things can lead to big ideas, and almost any novel concept is worth floating to clients. The tiny, free book lending kiosks sometimes officially branded “Little Free Libraries” are everywhere in my county, have become a non-profit initiative, and are driving Etsy sales of cute wooden contraptions. Moreover, my region is dotted with unstaffed farm stands that operate on the honor system, trusting neighbors to pay for what they take. I’d say our household purchases about half of our produce from them.

Within recent recall, the milkman and the grocery delivery boy seemed as distant as the phonograph. Now, consumers are showing interest in having whole meal kitsentire wardrobes, and just about everything delivered. The point being: don’t discount anything that renders convenience; not the traveling salesman, not the automat.

The decision to experiment with a kiosk isn’t a simple one. There will be financial aspects, like how to access a unit that works for the inventory being sold. There will be security questions, as most businesses probably won’t feel comfortable operating on the honor system.

But if the question is whether there is an appetite for the right kiosk, selling the right goods, in the right place, I’ll close today with a look at these provocative, illuminating reviews from just one location of Farmer’s Fridge:

Screenshot: Multiple positive five-star Yelp reviews praising existing kiosks

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Friday, November 1, 2019

Hypothesis Testing in SEO & Statistical Significance - Whiteboard Friday

Posted by Emily.Potter

A/B testing your SEO changes can bring you a competitive edge and dodge the bullet of negative changes that could lower your traffic. In this episode of Whiteboard Friday, Emily Potter shares not only why A/B testing your changes is important, but how to develop a hypothesis, what goes into collecting and analyzing the data, and thoughts around drawing your conclusions.

Click on the whiteboard image above to open a high resolution version in a new tab!

Video Transcription

Howdy, Moz fans. I'm Emily Potter, and I work at Distilled over in our London office. Today I'm going to talk to you about hypothesis testing in SEO and statistical significance.

At Distilled, we use a platform called ODN, which is the Distilled Optimization Delivery Network, to do SEO A/B testing. Now, in that, we use hypothesis testing. You may not be able to deploy ODN, but I still think today that you can learn something valuable from what I'm talking about.

Hypothesis testing

The four main steps of hypothesis testing

So when we're using hypothesis testing, we use four main steps:

  1. First, we formulate a hypothesis.
  2. Then we collect data on that hypothesis.
  3. We analyze the data, and then... 
  4. We draw some conclusions from that at the end.

The most important part of A/B testing is having a strong hypothesis. So up here, I've talked about how to formulate a strong SEO hypothesis.

1. Forming your hypothesis

Three mechanisms to help formulate a hypothesis

Now we need to remember that with SEO we are trying to look to impact three things to increase organic traffic.

  1. We're either trying to improve organic click-through rates. So that's any change you make that makes yours appearance in the SERPs seem more appealing to your competitors and therefore more people will click your ad.
  2. Or you can improve your organic ranking so you're moving higher up.
  3. Or we could also rank for more keywords.

You could also be impacting a mixture of all three of these things. But you just want to make sure that one of these is clearly being targeted or else it's not really an SEO test.

2. Collecting the data

Now next, we collect our data. Again, at Distilled, we use the ODN platform to do this. Now, with the ODN platform, we do A/B testing, and we split pages up into statistically similar buckets. 

A/B test with your control and your variant

So once we do that, we take our variant group and we use a mathematical analysis to decide what we think the variant group would have done had we not made that change.

So up here, we have the black line, and that's what that's doing. It's predicting what our model thought the variant group would do if we had not made any change. This dotted line here is when the test began. So you can see after the test there was a separation. This blue line is actually what happened. 

Now, because there's a difference between these two lines, we can see a change. If we move down here, we've just plotted the difference between those two lines.

Because the blue line is above the black line, we call this a positive test. Now this green part here is our confidence interval, and this one, as a standard, is a 95% confidence interval. Now we use that because we use statistical testing. So when the green lines are all above the zero line, or all below it for a negative test, we can call this a statistically significant test.

For this one, our best estimate is that this would have increased sessions by 12%, and that roughly turns out to be about 7,000 monthly organic sessions. Now, on either side here, you can see I have written 2.5%. That's to make this all add up to 100, and the reason for that is that you never get a 100% confident result. There's always the opportunity that there's a random chance and you have a false negative or positive. That's why we then say we are 97.5% confident this was positive. That's because we have 95 plus 2.5.

Tests without statistical significance

Now, at Distilled, we've found that there are a lot of circumstances where we have tests that are not statistically significant, but there's pretty strong evidence that they had an uplift. If we move down here, I have an example of that. So this is an example of something that wasn't statistically significant, but we saw a strong uplift.

Now you can see our green line still has an area in it that is negative, and that's saying there's still a chance that, at 95% confidence interval, this was a negative test. Now if we drop down again below, I've done our pink again. So we have 5% on both sides, and we can say here that we're 95% confident there was a positive result. That's because this 5% is always above as well.

3. Analyze the data to test hypothesis

Now the reason we do this is to try and be able to implement changes that we have a strong hypothesis with and be able to get those wins from those instead of just rejecting it completely. Now part of the reason for this is also that we say we're doing business and not science.

Here I've created a chart of when we would maybe deploy a test that was not statistically significant, and this is based off how strong or weak the hypothesis is and how cheap or expensive the change is.


Strong hypothesis / cheap change

Now over here, in your top right corner, when we have a strong hypothesis and a cheap change, we'd probably deploy that. For example, we had a test like this recently with one of our clients at Distilled, where they added their main keyword to the H1.

This final result looked something like this graph here. It was a strong hypothesis. It wasn't an expensive change to implement, and we decided to deploy that test because we were pretty confident that that would still be something that would be positive.

Weak hypothesis / cheap change

Now on this other side here, if you have a weak hypothesis but it's still cheap, then maybe evidence of an uplift is still reason to deploy that. You'd have to communicate with your client.

Strong hypothesis / expensive change

On the expensive change with strong hypothesis point, you're going to have to weigh out the benefit that you might get from your return on investment if you calculate your expected revenue based off that percentage change that you're getting there.

Weak hypothesis / cheap change

When it's a weak hypothesis and expensive change, we would only want to deploy that if it's statistically significant.

4. Drawing conclusions

Now we need to remember that when we're doing hypothesis testing, all we're doing is trying to test the null hypothesis. That does not mean that a null result means that there was no effect at all. All that that means is that we cannot accept or reject the hypothesis. We're saying that this was too random for us to say whether this is true or not.

Now 95% confidence interval is being able to accept or reject the hypothesis, and we're saying our data is not noise. When it's less than 95% confidence, like this one over here, we can't claim that we learned something the way that we would with a scientific test, but we could still say we have some pretty strong evidence that this would produce a positive effect on these pages.

The advantages of testing

Now when we talk to our clients about this, it's because we're aiming really here to give a competitive advantage over other people in their verticals. Now the main advantage of testing is to avoid those negative changes.

We want to just make sure that changes we're making are not really plummeting traffic, and we see that a lot. At Distilled, we call that a dodged bullet.

Now this is something I hope that you can bring into your work and to be able to use with your clients or with your own website. Hopefully, you can start formulating hypotheses, and even if you can't deploy something like ODN, you can still use your GA data to try and get a better idea if changes that you're making are helping or hurting your traffic. That's all that I have for you today. Thank you.

Video transcription by Speechpad.com


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