Monday, June 18, 2018

Eight steps for a bulletproof local search strategy

Appearing in local searches is something businesses need to be taking very seriously. The rise of mobile has made this concept even more prevalent. In fact, a study by Google found that 88% of ‘near me’ searches were conducted on a mobile device.

It’s important to realize that ranking on a local search (in any capacity) is no overnight job. Local SEO is extremely competitive and when it comes to any sort of SEO strategy, there is one thing to keep in mind: it changes constantly.

There are many different factors that come into play when etching out a name for yourself in the local market. Here are eight fundamental steps to get you started.

Prioritize titles and meta description tags

Titles and meta description tags are customizable elements that let users know what your website, or webpages, are about. Remember, most users scan the results of online searches very quickly, so these descriptions should be concise and easily absorbed.

When looking at title tags:

  • The typical title length is between 50 and 60 characters
  • Meta descriptions are between 160 and 200 characters
  • Each word needs be used strategically to give the user exactly what they want to know.

If you use WordPress, you can easily preview and analyze the descriptions of your web pages using the Yoast SEO Plugin.

If you want to attract local searches, be sure to include the name of the city or geographic area that you are targeting and try to position the keyword as near to the beginning as possible.

Writing titles and meta descriptions is an art form: you need to make every single element matter.

Use online directories and citations

Businesses now have access to all sorts of high-traffic online directories, including:

  • Citysearch
  • Angie’s List
  • Yelp.

Getting your business listed on these sites is one of the best ways to improve local rankings. The primary bits of information to register are:

  • Business name
  • Address
  • Phone number
  • Website URL
  • Hours in operation
  • Services offered
  • Credentials
  • Photos.

Be sure to update these accurately and consistently across the respective directories. Any errors or differentiation that make the information tough for Google to determine can have serious negative effects.

Google My Business: claim and optimize

Other than the major directory sites, one of the most important things local businesses can do is claim their company on Google My Business. If properly optimized, this is an incredible opportunity to gain exposure on the Google 3-Pack.

The verification process is simple. Google will send you a PIN to verify your business, then all you need to do is log in to Google My Business and enter the PIN number. This proves to Google that your business is legitimate. Once verified, you can optimize your description and all the necessary information to help customers learn more.

Actively pursue online reviews

It’s no secret that online reviews play a big role in purchasing decisions these days. In fact, studies have found that 84% of consumers trust them, just as much as personal recommendations.

Google also recognizes their importance and factors them into your rankings. Therefore, getting positive reviews needs to be something you are consistently pursuing. Keep in mind that you may need to ask customer to complete a review. You should also consider doing the following:

  • Outline your goals. How many reviews do you want each month?
  • Determine KPIs
  • Identify effective ways to follow up with customers for reviews
  • Know how employees/customer service will factor in
  • Have an approach to continuously optimize.

Software solutions like Trustpilot, Vendasta, and Get Five Stars are great for gaining and managing online reviews.

Social media and Google are the primary channels people look to in terms of reading reviews.

Your business’ Facebook and Google My Business pages are the two areas in which you should be focusing the bulk of your efforts – as reviews here are influential in boosting online visibility.

Produce local content

If you want to rank locally, you must produce high quality content that pertains to your area of operation. This can be through blog posts, online Q&As, or any other type of page that is specific to the local area. For written content, it’s best to keep the length in the ballpark of 1000 words.

When writing content, there are a number of factors to think about:

  • Understand your ideal customer
  • Know when and where they consume content
  • Align with the buyer’s journey
  • Keep your messaging consistent
  • Publish at a steady pace
  • Promote across your channels.

If you have a number of different locations, it’s a wise move to set up separate landing pages for each.

Creating and distributing branded content is one of the key methods for differentiating yourself in the market. With whatever you produce, be sure your messaging is relevant, informative, and actionable.

Use local structured data markup

Structured data markup, or ‘schema markup’, is a code added to your website that gives the search engine robots the necessary information about your business. This can be in relation to the products or services you offer, reviews, or what your content is about, for example.


As barely 30% of the businesses do this, adding appropriate markup is one of the best ways to make a local business stand out among the crowd. Google has a user-friendly testing tool that allows you to check your markup and ensure it’s implemented correctly. Google’s Data Highlighter also makes this process even easier.

Local SEO is all about making life more convenient for the users. This concept also applies to the search engine crawlers.

Be socially active

Social media is dominating the business atmosphere for business and consumers alike. With nearly one third of the world’s population being active on at least one of the major platforms, businesses need to make it a point to remain active, especially within their local market. There are many things you can do in this regard.

  • Post about local topics
  • Consistently publish engaging content
  • Share content
  • Get content shared
  • Interact with locals
  • Keep followers in the loop.

Search engines like to see that you are taking the time to engage with the world around you and on social media. In return, your profile will be more visible to local users. If you’re not taking advantage of this, it’s a safe bet that your competitors are.

Show community spirit

Long before the days of the internet, showing interest in the local community was one of the best ways to gain exposure, build relationships, and convey what the main purpose of your business. This idea still holds true, even today; the only difference is that the tools and landscapes to do so are different.

There are all kinds of activities that you can use to get your name out there in the community. Sponsoring events from time to time is a great way to get mentioned in local content/news. Making it clear that you are dedicated to serving the area can be an influential factor in improving your rankings.

Over to you

Following these steps to improve local SEO is not a one-off action; ranking high in the SERPS requires strong and persistent efforts. Furthermore, you will need to keep an eye out for new trends and how to capitalize accordingly. As the search engines are constantly changing, knowing what to do when an update is rolled out should be pre-defined.


Manish Dudharejia is the President and Founder of E2M Solutions Inc.


Friday, June 15, 2018

A guide to HTML & meta tags in 2018

We’ve previously covered HTML meta tags & meta tags here and in some depth here, but as with most things in SEO, it’s an ever-changing landscape and the accepted usage and definitions of tags is often changing.

It’s worth mentioning that if you’re in this realm of SEO optimization, you should also be getting the low-down and implementing structured data to ensure crawlers get the best experience possible.

HTML meta tags vs meta tags – what’s the deal?

Firstly, it’s time to clear up some of the confusion around HTML meta tags and meta tags.  The difference between the two tag types is largely arbitrary, with the syntax for an HTML meta tag meaning it’ll contain the word meta within it, whereas a tag defined as a meta tag doesn’t necessarily have to.

The decision for which do or don’t are defined by W3C and are open to change over time, however, what’s important for us to remember is that they both serve the same purpose, that is which is that they are used to provide search engines with information about a web page

Sidenote: Some people include header tags as meta tags, but as they describe one element of a page, not the contents of a page as a whole, we’ve decided to leave them out. However, it goes without saying that ensuring you’re optimizing your header tags will help search engines, and more importantly users, understand what your content is about.

With that cleared up, we can get down to business and take a look at a selection of both HTML and meta tags that we think are useful when performing SEO.


So to start off on the wrong foot, the Hreflang tag isn’t technically a tag. It is an attribute, but it is an important attribute that can help tell Google which language you’re content is using on a webpage.

If you have a site which uses multiple translations, or that serves different territories, you should definitely use Hreflang to ensure that the correct language version is being served in the correct versions of Google. This can help search engines rank your content better, and more importantly ensures users in different territories get the right experience.

An example code snippet for targeting a webpage at English language users in the UK:

<link rel=”alternate” href=”; hreflang=”en-gb” />

Canonical tag

Another very important one is the canonical tag. Set it up incorrectly and you risk losing visibility in the SERPs and causing real issues for your site. Used correctly, however, it’s a great way of telling search engines that a webpage URL is the defacto version. It’s the best way to avoid duplicate content issues on your site, caused by search engines crawling multiple URLs that contain the same or close to identical content on them.

In general, if a search engine finds multiple URLs with identical content, it’ll have a harder job determining which is the original and which is the duplicate. This can lead to lower rankings for both, or worse, an important page won’t rank.

An example code snippet for canonical tag use:

<link rel=”canonical” href=”; />

Content type tag

The content type tag is used for defining a pages content type and the character set it uses. Using this helps your browser understand and decode a page, and is therefore important.

An example code snippet for content type tag use:

<meta http-equiv=”Content-Type” content=”text/html; charset=utf-8″ />

Title tag

Probably one of the more recognizable and used tags for anyone carrying out SEO work. The title tag is used to specify what the web page is about. They’re displayed in your browser tab to give users a steer, and more importantly are used by search engines to generate the results we see in the SERPs.


From an SEO perspective, optimizing your title tag to contain topics/keywords information about the contents on the page can help to improve your rankings for those topics/keywords. Currently you can expect Google to display between 50-60 characters of your title before it’s truncated, so keep an eye on length when writing these.

An example code snippet for the title tag, which sits within the head tag at the top of your webpage:

<title> | The best examples on the web</title>

Meta description tag

Similar to the title tag, the meta description tag is well known and provides you with an opportunity to tell search engines and users in the SERPs what your webpage content is about. While not a direct ranking factor, you should optimize your meta description to provide a compelling succinct account of your web pages content.

If Google doesn’t think you’ve done a good enough job, they may choose to replace your meta description tag with their own interpretation, often using content from the opening few paragraphs of your site.

An example code snippet for meta description tag:

<meta name=”description” content=”This is a meta description”>

Viewport tag

The viewport tag is a useful tag for helping browsers understand and control the dimensions of your web page.

In the past, there was no need for this tag as everyone viewed webpages on desktop on similar sized displays, but with the rise and rise of mobile and tablet usage, many of which have different dimensions, it’s now more important to ensure that you’re telling the browser this information.

Correct implementation of the viewport tag will ensure that users experience your site in the correct way, and if there are

An example code snippet for the viewport meta tag:

<meta name=”viewport” content=”width=device-width, initial-scale=1″>

Robots meta tags

There’s a large number of robot meta tags you can use, all of which will help search engine crawlers do their job of crawling and indexing web pages across the internet. Not all search engines will follow all commands, but below are a few examples of robot meta tags and what they ask the crawlers to do:

Nofollow Tells crawlers not to follow any of the links listed on that page, and also not to pass any equity to linked page
Noindex Tells crawlers not to index that page
Noimageindex Tells crawlers not to index images from that page
Noarchive Tells crawlers not to include a cached version

An example code snippet for the robot meta tag:

<meta name=”robot” content=”noindex, nofollow”>

Open graph (OG) meta tags for social

Finally, we have the OG meta tags for social. While less a direct focus for SEO, ensuring you have correctly implemented OG meta tags for social can help ensure your content looks great when it’s shared, can help to improve engagement with posts and ultimately increase traffic.

<meta property=”og:title” content=”Article about tags”/>
<meta property=”og:image” content=”>
<meta property=”og:site_name” content=”SEO blog”/>
<meta property=”og:description” content=”This article will talk about tags”/>

Needless to say, there are a range of other tags you can use on your website, and this list isn’t exhaustive, but hopefully gives you a steer on some of the more important and useful tags you can use on your website to make it the experience better for both search engines and crawlers.


Joshua is an SEO specialist and strategist at atom42


Thursday, June 14, 2018

Google’s ‘More Results’ button: a search marketer’s POV

I have written extensively about how Google is continually making its SERPs richer, more feature-led, and increasingly intuitive.

Of course this is happening on desktop, but how the SERPs are being displayed across mobile devices deserves special attention from marketers. It’s a space that presents its own challenges and opportunities. It is also highly competitive and evolving in a unique way.

One such change to Google’s mobile SERPs in recent months is the launch of its ‘More Results’ button (MR). I spoke to Adthena’s Ashley Fletcher about the MR tweak, his reaction to it, and how he sees mobile search changing throughout 2018 and beyond.

Competitive intelligence

Fletcher’s interest in the evolving landscape of the SERPs goes back 13 years to when SEO was in its infancy. Since then, he has worked within agencies, on the client side at Criteo and Beatthatquote, at Google itself (launching its insurance comparison tools in the US and UK), and now at Adthena as VP of marketing.

Adthena specializes in competitive intelligence – using artificial intelligence (AI) and gathering unparalleled levels of data about the SERPs. “There’s so many moving parts in paid search campaigns at scale,” Fletcher tells me. “Retailers might have 1000 product lines. That’s 1000 battlegrounds. AI and tech helps give a clear picture of these battlegrounds.”

Decluttering the SERPs

The quest for clarity amid the SERPs is not exclusive for companies like Adthena and its clients however. Google’s decision to include the MR button could well be partly attributed to cleaning up the mobile search space. This is something Fletcher agrees with, and it is in keeping with other tweaks from the search giant.

“It’s quite a subtle change,” he says. “But there’s such an influx of ad units on mobile SERPs, it is quite cluttered. It seems the MR button is part of a bigger move by Google to streamline the mobile SERPs.”

Better usability

We know that user experience is high on Google’s agenda. A more efficient UX on the SERPs gets us to the information we desire, the product we want, or the destination we want to visit as soon as possible. This keeps us satisfied and keen to return to Google again, and again, down the line.

Fletcher notes more than a passing resemblance between the MR button and the way content is navigated by users on social media. “We’re seeing Google trying to encourage a sort of infinity loop,” he says. “It’s a single page UX more like what we see on the Facebook newsfeed or on Instagram. Users – and mobile users especially – are now very used to scrolling the same page forever rather than clicking through numerous pages.”

This is a curious realization. The notion of Google wanting users to ‘scroll forever’ is surely counter to the overarching agenda of keeping things as efficient as possible.

But as Fletcher highlights, sometimes the SERP doesn’t do the job and the MR button is a faster way of perusing other search results. It is more in-keeping with dominant trends of mobile navigation, and thus more accepted. There is now no need to load page two of the SERPs. “Page 2 is a graveyard anyway,” Fletcher says.

Impacts: clicks, rankings and happier users

The MR button is quite a subtle design change on Google’s mobile SERPs, but Fletcher and Adthena are already noticing a change in CTRs.

“We’re expecting CTRs to climb on paid and organic listings,” Fletcher says. “It’s what we’re seeing in our latest Paid Search Benchmark report and I would think it will continue.”

Indeed, Adthena’s recently published benchmark is already seeing average CTRs up 10% toward the end of 2017, compared to around 3% for desktops. As the report states, it’s “a measure of the robustness of paid search, and an indicator that advertisers are continuing to get value from the channel”.

If it continues, this will be welcome news to search marketers and SEOs who are striving to ensure their content is getting clicks and keeping users engaged.

“Google rewards pages with good high CTRs and low bounce rates,” Fletcher adds. “And the overall result is simpler SERPs and happier users.”

Takeaways: mobile search is still a battleground

While the MR button has – in effect – eliminated the second page (and beyond) of mobile SERPs, it will still be best practice for marketers to want to be visible above it in the same way page one is still favoured on desktop.

As Fletcher points out: “Beyond the ‘more results’ button is still a graveyard. Search advertisers know this, and they know that they still have to keep up to retain visibility above the fold.”

With the addition of features such as the MR button, the number of battlegrounds that search marketers need to have an understanding and clear view of is not going down – whether across mobile or desktop, more numerous key phrases, within paid search, in organic listings, or across maps on a local and even hyperlocal level.

The SERPs are continuing to diversify, but ultimately, the users are reaping the benefit. With tweaks like MR, Google as a tool is even more efficient and intuitive. The power of mobile search – even with the limitations of the small screen – is being further refined to meet its capabilities.

Wednesday, June 13, 2018

SEW Interview: Clark Boyd on visual search

We recently caught up with Clark Boyd, a visual search expert and regular contributor to Search Engine Watch. We discussed camera-based visual search – that futuristic technology that allows you to search the physical world with your smartphone – what it means for the way search is changing, and whether we’re going to see it become truly commonplace any time soon.

In case any of our readers aren’t up to speed on what ‘camera-based visual search’ actually is, we’re talking about technology like Google Lens and Pinterest Lens; you can point your smartphone camera at an object, the app will recognize it, and then perform a search for you based on what it identifies.

So you can point it at, for example, a pair of red shoes, the technology will recognize that these are red shoes, and it’ll pull up search results – such as shopping listings – for similar-looking pairs of shoes.

In other words, if you’ve ever been out and about and seen someone with a really cool piece of clothing that you wish you could buy for yourself – now you can.


First of all – what’s your personal take on camera-based visual search – the likes of Google Lens and Pinterest Lens? Do you use these technologies often?

I have used visual search on Google, Pinterest, and Amazon quite a lot. For those that haven’t used these yet, you can do so within the Google Lens app (now available on iOS), the Pinterest app, and the Amazon app too.

In essence, I can point my smartphone at an object and the app will interpret it based on what it sees, but also what it assumes I want to know.

With Google, that can mean additional information about landmarks pulled from the Knowledge Graph or it might show me Shopping links. On Pinterest it could show recipes if I look at some ingredients, or it can go deeper to look at the style of a piece of furniture, for example. Amazon is a bit more straightforward in that it will show me similar products.

I suppose that visual search is best summarized by saying it’s there when we don’t have the words to describe what we want to know. That could be an item of clothing, or we could be looking for inspiration – we know what the item is, but we aren’t 100% sure what would go with it.

Recently, I have been both decorating a house and planning my wedding. As a colorblind luddite with more enthusiasm than taste, I can use visual search to help me plan. Simply typing a text search for [armchairs] is going to lead me nowhere; scanning a chair I like to find similar items and also complementary ones is genuinely useful for me.

At the moment, this works best on Pinterest. It uses contextual signals (Pins, boards, feedback from similar users) to pick up on the esthetic elements of an object, beyond just shape and color. Design patterns and texture are used to deliver nuanced and satisfactory items in response to a query.

What’s interesting is that camera-based searches on Pinterest deliver different results to text-based searches for similar items. Basically, visual search can often lead to better results on Pinterest. That’s not the case on Google yet, but that’s where they are aiming to get to.

And that’s the key, really: in some contexts, visual search adds value for the user. It’s easy to use and can lead to better results. There are now over 600,000,000 visual searches on Pinterest every month, so it seems people are really starting to engage with the technology.

To my mind, that is what will give visual search longevity. It mimics our thought process and augments it, too; visual search opens up a whole new repository of information for us.


Camera-based visual search has some fairly obvious applications in the realm of ecommerce, for example where you can see something while you’re on the go and instantly pull up search results showing you how to buy it. But do you think there are any other big potential uses for visual search?

I think there are lots of potential uses, yes; in fact, even the ecommerce example really only scratches the surface.

Where visual search comes into its own, and I think goes beyond the realm of the purely novel, is when it suggests new ideas that people have not yet thought of.

Pinterest’s Lens the Look tool is a great example. I could search for shoes and find the pair I wanted, but Pinterest can also suggest an outfit that would go with the shoes too. This then becomes more of an ongoing conversation.

The new app from fashion retailer ASOS will likely go in this direction too, and I expect sites like Zara and H&M to follow suit. IKEA has its AR-tinged effort too, which allows people to see how the furniture will look. Although in my experience, it will lie in a million pieces for days until I figure out how to put it all together!

We should always consider that visual search exists at a very clear intersection of the physical and the digital. As a result, we should also think about the ways in which we can make it easier for people to enhance their experience of our stores through visual search.

We have seen things like QR codes linger without ever really taking off here, and Pinterest has launched Pincodes as a way to try and get people to engage.

Google has started adding features like this to its Lens tool, and the recent announcement about voice-activated Shopping through Google Express is another step in that direction.

The core of this is really to get people on board first and foremost, and then to introduce more overt forms of ecommerce.

Beyond that, visual search can allow us to take better pictures. Google has demonstrated forthcoming versions of Lens that will automatically detect and remove obstructions from images, and input Wifi codes just by showing the camera the password.

What we’re really looking for are those intangibles that only an image can get close to capturing. So anything related to style or design, such as the visual arts or even tattoos (the most searched for ‘item’ on Pinterest visual search), will be a natural fit.

Search has been a fantastic medium when we want to locate a product or service. That input format limits its reach, however. If search is to continue expanding, it must become a more comprehensive resource, actively searching on our behalf before we provide explicit instruction.


We’ve seen a lot of development in the realm of visual search over the past couple of years, with tech companies like Google, Pinterest and Bing emerging as front-runners in the field. Google acquired an image recognition start-up, and Pinterest hired a new Head of Search and started more seriously developing its search capabilities. What do you think could be coming next for visual search?

First of all, the technology will keep improving in accuracy.

Acquisitions will likely be a part of this process. Pinterest’s early success can be put down to personnel and business strategy, but they also bought Kosei in 2015 to help understand and categorize images.

I would expect Google to put a lot of resource into integrating visual search with its other products, like Google Maps and Shopping. The recent I/O developers conference provided some tantalizing glimpses of where this will lead us.

Lens is already built into the Pixel 2 camera, which makes it much easier to access, but it still isn’t integrated with other products in a truly intuitive way. People are impressed when their smartphone can recognize objects, but that capability doesn’t really add long-term value.

So, we will see a more accurate interpretation of images and, therefore, more varied and useful results.

To go back to the example of my attempts to help furnish an apartment, I don’t think where we are today is by any means the fulfillment of visual search’s promise. I can certainly imagine a future where I can use visual search to scan the space in my living room, take into account the dimensions and act as my virtual interior designer, recommending designs that fit with my preferences and budget. AR technology would let me see how this will look before I buy and also save the image so I can come back to it.

The technologies to do that either exist or are getting to an acceptable level of accuracy. Combined, they could form a virtual interior design suite that either brands or search engines could use.

A gap still remains between the search engine and the content it serves, however.

For this to function, brands need to play their part too. There are plentiful best practices for optimizing for Pinterest search and all visual search engines make use of contextual signals and metadata to understand what they are looking at.

One way this could happen is when brands team up with influencers to showcase their products. As long as their full range is tied thematically to the products on show, these can be served to consumers as options for further ideas.

In summary, I think the technology has a bit of development still to come, but we need to meet the machine learning algorithms halfway by giving them the right data to work with. Pinterest has used over one billion images in its training set, for example. That means taking ownership of all online real estate and identifying opportunities for our content to surface through related results.

The advertising side of this will come, of course (and Pinterest is evolving its product all the time), but for this to come to fruition it also requires a shift in mindset from the advertisers themselves. The most sophisticated search marketers are already looking at ways to move beyond text-based results and start using search as a full-funnel marketing channel.



We’ve been talking about visual search mostly in the context of smartphones, as currently that’s the technology most immediately suited to searching the physical world, given that all smartphones these days have built-in cameras.

But what about other gadgets? We’re seeing a lot of companies at the moment who are developing smart glasses or AR glasses – Snap, Intel, Toshiba came out with a pair just a few months ago – could visual search find a natural home there?

I’m not sure we’ve seen the end of Google Glass, actually. I really don’t think Google is finished in that area and it does make sense to have visual search incorporated directly into our field of vision.

The most likely area to take off here in terms of usage in the short-term is actually for the visually impaired. There are smart glasses that use artificial intelligence (AI) to perform visual searches on objects and highlight immediately what they are seeing.

Those are from a company called Poly, who are doing a range of interesting things in this space.

We think of devices that we wear or actively use, but that may not even be the long-term future of visual search. Poly has also developed visual search technology that works in stores. It can keep track of inventory levels automatically, but also detects who is in the store by linking with the Bluetooth connection in their phone.

Things like face IDs on smartphones along with Apple/Google Pay really help to create this potential use.

So the visual search exists at a higher level, it detects who is in the store, and it adds items to their basket as they pick them up. When the person leaves, they are charged via Apple/Google Pay or similar. So a bit like the Amazon Go stores, but using visual search to scan the store and see who is there and what they buy.

The cost for doing this has reduced dramatically, so it would now be possible for smaller stores to engage with this technology. Where that has potential to take off is in its introduction of a friction-free shopping experience.

That’s just one potential use, but it highlights how visual search can lead to much bigger opportunities for retailers and customers.

How close we are to that reality depends on people’s proclivity to accept that level of surveillance.


The most futuristic technology in the world is no good if no-one is using it, and we’ve seen much-vaunted tech advancements flop before – speaking of smart glasses, Google Glass is a good example of that. So what would you say are the immediate barriers to the more widespread adoption of visual search? What kind of timeline are we looking at for visual search entering the mainstream – if indeed it ever does?

With voice search, it was always stated that 95% accuracy would be the point at which people would use the technology. I don’t think there have been excessive studies into visual search yet, but that should come soon. With increased accuracy will come widespread awareness of the potential uses of visual search.

The short-term focus really has to be on making the technology as useful as it can be.

Once the technology gets closer to that 95% accuracy mark, the key test will be whether novelty use turns into habit. The fact that over 600,000,000 visual searches take place on Pinterest each month suggests we are quickly reaching that point.

It also has to be easy to access visual search, because the moments in which we want to use it can be quite fleeting.

From there, it will be possible for retailers, search engines, and social media platforms like Instagram and Pinterest to build out their advertising products.

As with any innovation, there is a point of critical mass that needs to be reached, but we are starting to see that with voice search and the monetization of visual search sits rather more naturally, I think.

We want to understand the world around us and we want to engage with new ideas; images are the best way to do this, but they are also a difficult form of communication.

Our culture is majoritively visual and has been for some time. We need only look at the nature of ads over the past century; text recedes as imagery assumes the foreground in most instances.

Whether the Lens technologies are an end in themselves or just a stage in the development of visual search, we can’t be sure. There may be entirely new technologies that sit outside smartphones in the future, but image recognition will still be central.

I would still encourage all marketers to embrace a trend that only looks likely to gather pace.


Visual search is still quite an abstract concept for most of us, so is there anything practical that marketers and SEOs can do to prepare for it? Is it possible to optimize for visual search just yet? If marketers want to try and keep ahead of the visual search curve, what would be the best way to do that?

Any time we are dealing with search, there will be a lot of theory and practice that can help anyone get better results. We just don’t have the shortcuts we used to.

When it comes to visual search, I would recommend:

  • Read blogs like Pinterest engineering. It can seem as though these things work magically, but there is a clear methodology behind visual search
  • Organize your presence across Instagram, Google, Pinterest. Visual search engines use these as hints to understand what each image contains.
  • Follow the traditional image search best practices.
  • Analyze your own results. Look at how your images perform and try new colors, new themes. Results will be evermore personalized, so there isn’t a blanket right or wrong
  • Consider how your shoppable images might surface. You either want to be the item people search for or the logical next step from there. Look at your influencer engagements and those of your competitors to see what tends to show up
  • Engage directly with creative teams. Search remains a data-intensive industry and always will be, but this strength is now merging with the more creative aspects. Search marketers need to be working with social media and brand to make the most of visual search
  • Make it easy to isolate and identify items within your pictures. Visual search engines have a really tough job on their hands; don’t make it harder for them
  • Use a consistent theme and, if you use stock imagery, adapt it a bit. Otherwise, the image will be recognized based on the millions of other times it has appeared
  • Think about how to optimize your brick-and-mortar presence. If people use products as the stimulus for a search, what information will they want to know? Price, product information, similar items, and so on. Then ensure that you are optimized for these. Use structured data to make it easy for a search engine to surface this information. In fact, if there’s one thing to focus on for visual search right now, it is structured data.


Check our Clark’s presentation on visual search here.

Four ways you can use AI to optimize your AdWords campaigns

Artificial intelligence (AI) and machine learning algorithms are mainstreaming in a way that was never before possible, and these changes are having a significant influence on the way in which marketers need to approach search advertising.

In addition to AdWords itself incorporating AI into its framework, new opportunities are arising that can give marketers an edge over their competitors, or automate lower-level tasks, freeing up more time for strategy.

Here are four ways you can start taking advantage of AI to make the most of your AdWords campaigns.

Automated bidding

Automated machine learning as a solution to the decision of what price to bid on paid advertising is becoming an increasingly popular option as the necessary technologies become available to more firms.

Bidding too low means missing out on opportunities to reach leads, while bidding too high means sacrificing ROI.

Google’s internal automated bidding, on top of being identical to what everybody else is using, doesn’t have access to the information it needs in order to maximize your ROI. Reaching that goal also requires knowing consumer trends, purchase behavior, seasonality, demographics, customer lifetime value, and more.

A successful automated bidding model must:

  • Estimate the price elasticity of each ad by using statistical inference based on previous bids
  • Factor in the actual value expected by a click from each individual ad based on previous clicks
  • Iterate in response to new data
  • Recognize changes in the bidding landscape or the performance of visits and adapt quickly, rather than falsely assuming past performance will predict future performance in all circumstances.

There are, however, some things to look out for:

  • Models that don’t know what’s happening on your site will make bad inferences. For example, if you test a new landing page and it turns out to lower your ROI, your model could start bidding lower on those keywords. After replacing the landing page with a better one, the model may still get stuck bidding low on the keywords, because there isn’t enough new data available to push the bids back up
  • Models that rely too heavily on statistical significance may test a losing strategy for too long, but models that fail to incorporate statistical significance can throw away good opportunities while propping up flukes.
  • Watch out for feedback loops in your model. For example, you wouldn’t want your model to bid more on an ad with a high conversion rate if the only reason the conversion rate is high is because the high bids are increasing the conversion rate. These types of conflicts should be controlled for.

Pausing poorly performing ads

The quickest way to lose money in AdWords is to continue bidding on an ad that isn’t producing any ROI. When the clicks roll in but the sales don’t, this can be a disaster.

Similarly, when an ad is getting the bids but not the clicks, your quality score will suffer, and ultimately your ROI will follow suit.

A well-built machine learning algorithm will understand when it is necessary to pause an ad in order to avoid hurting your ROI or quality score.

Here are some important considerations your model must account for:

  • The model must not be so sensitive that it abandons ads before they have a chance to show ROI. It must use statistical inference to estimate potential losses and gains based on previous performance
  • Rather than pausing the full ad outright, the model should factor in individual segments that can be paused, such as traffic from mobile devices, certain browsers that are not producing revenue, times of day or days of the week that repeatedly do poorly, or ad variations that aren’t performing well.

Dynamic ads

AdWords’ Dynamic Search Ads are one piece of machine learning technology that currently come built-in with the platform, allowing anybody who is using AdWords to take advantage of it.

Dynamic Search Ads automatically generate headlines to capture a searcher’s attention. After uploading a list of landing pages that you want Google to generate dynamic ads for, Google will identify searches that are a good fit for your landing pages, then automatically generate ad content using phrases from your pages.

Google is also generating ad suggestions based on machine learning. These recommendations use models of prior performance to suggest changes to your ads that should boost your results.

But the possibilities for dynamic ads don’t end with what is native to AdWords.

Machine learning approaches can be used to create dynamic ad content that incorporates the following:

  • Mixing and matching copy, image, and audience with multivariate testing and evolutionary algorithms
  • Incorporating the influence of external factors such as the weather or time of day.

A few platforms experimenting with this kind of control include Sentient Ascend, IBM Watson, Zalster, and Refuel4.

Available platforms

The previous insights might make it sound like you’ll need data scientists and developers on your team in order to take advantage of what AI and machine learning have to offer, but this isn’t necessarily the case. While full-time dedicated AI staff are a good idea for big businesses, small and medium businesses can still take advantage of these emerging technologies with emerging products.

Here are just a few examples:

  • Acquisio: This machine-learning platform is designed to improve performance in AdWords, Bing, and Facebook ads by cutting CPC and CPA while raising clicks and conversions
  • Cognitiv: Uses deep learning to predict where best to spend your money, self-customizing for each brand based on historical data
  • Frank: In addition to AdWords and Facebook ads, Frank is connected to millions of publishers. It launches campaigns automatically and optimizes them by target audience, creative, and channel
  • Magnetic: Designed to automatically match audiences to inventory while optimizing bids and cracking down on fraudulent clicks
  • Quarizmi: One of few AI platforms that specifically bills itself as being for AdWords. The platform automates keyword discovery, creative, bids and campaigns
  • Trapica: Identifies audiences, matches them to creatives, optimizes bidding, and scales your campaigns.

No matter the platform, use the insights discussed to make informed decisions about what will work best for you.


As AI becomes mainstream within the PPC industry, marketers will need to begin shifting their areas of expertise away from micromanaging keywords and bid prices, and towards higher-level strategy. In the meantime, the techniques and platforms discussed still aren’t in use by the majority of your competitors, and taking advantage of that gap would be a wise move.