How are beacons going to affect search marketing?

Recently I’ve been reading a lot about the effects beacons and proximity marketing may have on search strategy.

(I actually work for a company that makes beacons and management software, so it’s not just me being boring).

I’ve found little doubt that it will bring some very fundamental changes to the way we reach customers, and the type of targeting and data management we’ll need to master in order to do things properly.

Although perhaps not in the way you might think…

Improving proximity results

Search Engine Watch has spoken about beacons a lot in the past, but just in case you need a refresher, a beacon is a tiny device that can transmit a signal to any Bluetooth device in range – phones, fitness bracelets, headphones, smartwatches etc.

Usually this happens through an app (although Google in particular are taking steps to remove this friction and enable direct device communication), and before the privacy police wade in, it’s all completely opt-in.

It certainly has some obvious ramifications for local search.

In the past, we’ve largely been limited to areas defined by map coordinates for localisation. These are fine for locating buildings, but not so hot once people actually enter a space.

Beacons have a big advantage here because they get that location down to an area a couple of metres across, and they allow you to transmit and receive data in realtime. If I’m standing by the apples in your supermarket, you can fire me a coupon.

I’m using that example on purpose by the way, and I’ll explain why in a moment.

Beacons don’t need to be interruptive

For marketers, there seems to be an assumption that beacons are an interruptive marketing tool.

Retail couponing is the most obvious use-case after all, but just as early ecommerce sites learned, couponing is no way to build a successful business. And as the publishing industry is learning, interruptive marketing… just isn’t very good really. People don’t like it in most cases.

As I say though, this is only an assumption. The real value of beacons is actually almost the complete opposite of interruptive.

It is in contextual interactions, which usually rely on either an active request from a user, or passive scanning and data aggregation by the person deploying the beacons.

In other words, if I visit a museum, download it’s app and enable push notifications while I’m there, then I’m actively searching for information abut my location.

If not, then I can still be monitored as an anonymous device that is moving around the museum. Once this data is collected, there is a lot of potential value. Maybe it’s time to move that Rodin statue to a more prominent position (possibly next to the gift shop).

Search will need to become hyper-relevant in an open beacon marketplace

So what does this mean for search?

Currently, a lot of local search isn’t that great. There are plenty of fine examples, but there is certainly an adoption curve, particularly for small businesses.

Do a quick search for something like ‘Bike shop, Shrewsbury’ and you can usually see which businesses have a lot of low-hanging SEO fruit that they just aren’t optimising for.

This is a missed chance, but it is usually being missed because of a lack of familiarity and time. People who are busy running a hardware store don’t often have time or money to really concentrate on good SEO.

As beacon deployment becomes more widespread (and it is going to be), this situation is going to change for the user on the ground. App networks and beacons deployed as general infrastructure in more locations mean that local optimisation is opened up to more players, with more resources. Why should our local bike store be wasting time optimising when Raleigh can be doing it for them?

Local SEO will begin to be a wider concern not for the locations themselves, but for the companies that sell through those locations. And those companies have the resources and processes available to start doing a really good job.

There is however, still a place for the location itself in all this, and that is in adding contextual value, which may not come from purely commercial campaigns.

Recently I visited Edgelands at the Barbican in London, where one of our clients has deployed beacons that guide visitors around the interesting (and slightly confusing) internal space.

The interesting thing here is that it occurs through sound, so that visitors are able to view their surroundings, rather than keeping their eyes glued to their phone screens. It adds context while keeping the visitor engaged with the physical space, rather than having the two vie for attention.

With the rise of experience stores, this is going to become a more important point of differentiation over the next few years. Customers won’t want distracting alerts and pop-ups, they’ll want something that provides a richer experience.

From the marketing side, providing these will become a way to deepen brand affinity as much as increase immediate sales.

Search is about to leave its silos behind

This makes location a strange, mixed bag for search. On one side, brands providing advertising through app networks and beacon fleets owned by third parties (in my opinion, telcos are currently best placed to handle and benefit from large scale deployment, as they already have large data networks and physical locations).

In many cases, this will be about hyper-localised PPC campaigns. On the other, locations providing realtime SEO, with a shifting set of keywords based on whatever is currently happening in-store (or in-museum, or in-restaurant for instance).

It means that we’ll have to get better at aligning our data and working out which signals really matter, and we’re going to need to get insanely good at management and targeting.

I hate to use this word, but search will need to become more holistic, and even more aligned with marketing. There’s a huge opportunity here for search marketers, customer experience, data management and more.

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17 inspirational examples of data visualization

We can all collect masses of data, but it only becomes genuinely useful when we use it to make a clear point.

This is where data visualization comes in. Showing data in context and using creativity to make that same data tell a story can truly bring the numbers to life.

There are a whole bunch of data visualization tools out there to help create your own, but here are some existing examples for inspiration.

A day in the life of Americans

This excellent visualization from Flowing data uses information from the American Time Use Survey to show what Americans are up to at any time of day.

What streaming services pay artists

This from the wonderful information is beautiful website, looks at how the major online streaming music services compare in terms of paying the musicians.

Two centuries of US immigration

This fantastic visualization from metrocosm shows the various waves of immigration into the United States from the 19th century to the present day.

US population trends over time

This gif from the Pew Research Center is a great example of how movement can be used to convey shifts and trends over time.

Why you should take the bus

The German town of Münster produced this series of images back in 1991 to encourage bus use. It’s beautifully simple showing the relative impact of the same number of people (72) on bicycles, in cars, or on a bus.

What happens in an internet minute?

This infographic from excelacom presents what happens online in 60 seconds, including:

• 150 million emails are sent.
• 1,389 Uber rides.
• 527,760 photos shared on Snapchat.
• 51,000 app downloads on Apple’s App Store.
• $203,596 in sales on Amazon.com.

US wind map

This moving visualization shows wind speed and direction in real time.

It looks great and is easy to understand, which is key to effect data visualization. This one comes from hint.fm.

Daily routines of creative people

I’ve always been pretty cynical about this ‘X things successful people do before breakfast’ stuff – as if by following this, people are suddenly going to become Steve Jobs or Albert Einstein.

However, this one from podio showing daily routines of creative people is very interesting. It won’t turn you into a great composer, but it’s a fascinating insight nonetheless.

The impact of vaccines

This is a series of visualizations from the Wall Street Journal, which shows the impact of vaccines on various infectious diseases.

It’s striking stuff, which clearly demonstrates the incredible positive impact of vaccination programs in the US.

London food hygeine

This is a great use of freely available data to provide useful information for the public.

The one million tweet map

This uses tweet data to present a geographical representation of where people tweet about topics. The example below is for ‘Brexit‘.

The fallen of WW2

This, from Neil Halloran is a cross between data visualization and documentary.

There are two versions of this. The video version you can see embedded below, and an interactive version.

People living on earth

A simple but very effective visualization of the world’s population, and the speed at which it increases.

The ultimate data dog

This, again from Information is Beautiful, uses data on the intelligence and other characteristics of dog breeds, plotting this against data on the popularity of various breeds from the American Kennel Club.

How much did band members contribute to each Beatles album? 

This from Mike Moore, shows the relative writing percentage for each Beatles album, as well as the contribution over time.

A day on the London Underground

From Will Gallia, who used data from a single day’s use of the London underground to produce this timelapse visualization.

Fish Pharm

This is from way back in 2010, and illustrates the fact that antidepressants and other pharmaceuticals are now showing up in fish tissue.

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Google’s Keyword Planner tool just became even more inaccurate

You’re probably familiar with the Keyword Planner tool, which is one of the best sources we have to spot opportunities and make the business case for an investment into paid or organic search campaigns.

One of the things it provides is guidance on the volume of searches for any given query. The numbers reported in the tool have always been somewhat vague. They are rounded up and numbers end with at least one zero. A pinch of salt has always been required when digesting the data.

It turns out that these numbers are now even more imprecise.

Jennifer Slegg spotted that Google has started to combine related terms, pooling them all together and reporting one (bigger) number.

No longer can you separate the data for keyword variants, such as plurals, acronyms, words with space, and words with punctuation.

As such it would be easy to get a false impression of search volumes, unless you’re aware of the change. No sudden jump in search queries, just an amalgamated number. Be warned.

Here are a couple of examples…

Bundling together anagrams and regional spellings

Lumping together plurals and phrases without spaces

The problem could be exacerbated by third party tools. Jennifer says:

“For those that don’t notice the change – or worse, pulling the data from tools that haven’t updated to take into account the change – this means that some advertisers and SEOs are grossly overestimating those numbers, since many tools will combine data, and there is no notification alert on the results to show that how Google calculates average monthly searches has been changed.”

So yeah, this isn’t exactly good news. In fact, I can’t think of any benefit to the end user, but Google has a history of obfuscating data, so perhaps it shouldn’t come as a surprise.

That said, it once again pushes the focus towards relevance and context rather than pure volume. Advertisers and content creators would do well to focus on optimising clickthrough rate and landing page performance, rather than just shotgun marketing.

Guesstimated data aside, you can use Search Console to make sense of actual performance. Map your page impressions to organic (or paid) positions and you’ll get a sense of how accurate the Keyword Planner data is for any given term.

It’s also worth remembering that there are seasonal factors at play with the reported data. Volumes shown are an approximate figure based on 12 months search data. You might get a better idea of more accurate monthly figures if you cross-reference data from with Google Trends, which will show seasonal spikes (February is a big month for flowers).

Keyword Planner replaced Google’s Keyword Tool and Traffic Estimator about three years ago. Users of the old tools initially complained about missing the broad match and phrase match options. Now, they’re going to miss even more detail around keywords and data.

Proceed with caution, as ever.

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7 Definitive Do’s and Don’ts of Google AdWords Pay Per Click

Using Google AdWords or Bing Advertising can be one of the most efficient and most effective ways to drive highly targeted traffic to your websites and/or landing pages in a relatively quicker time frame than other digital marketing campaigns. However, there is a cost involved as there is with other […]

The post 7 Definitive Do’s and Don’ts of Google AdWords Pay Per Click appeared first on Receptional.com.

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How do people view search engine results pages?

The F-shaped pattern has been the commonly understood way in which web users browse sites and search results. 

Has user behaviour changed since then, or have perhaps the changes that Google and others have made to the presentation of search results made a difference?

An eyetracking study carried out by ConversionXL looks into this question, comparing the results with previous studies.

Here are a few key findings from the article…

The F-pattern no longer holds up

The F-pattern was something discovered during testing by Jakob Nielsen. The finding being that users read or scan pages in two horizontal movements followed by a vertical movement. Thus the F-shape.

For search results, as in the example shown on the right below (this is from 2006) we can see that the first two or three results attract most attention, while results below four or five downwards attract less interest.

Now the SERPs are different. We have more images to catch the eye in some results, as well as features like rich snippets, which stand in contrast to the more text-heavy Google results of the past.

Perhaps as a result of this ConversionXL were unable to replicate the F-shape in their tests. In the example below, the first result gets the maximum attention, with very little below the third result.

Google was right to remove right hand side ads

Google’s removal of right hand side ads earlier this year is backed up by the study.

In a nutshell, ads on the right didn’t get much attention, but ads at the top of search results did, at least until users realised they were ads (explains the green text I’d say).

Contrasts between Bing and Google

The study found a few differences in user behaviour on the two search engines:

• Users took longer before exploring below the fold on Bing. Google users began to view below the fold after around 7.1 seconds. On Bing this figure was 10.5 seconds.
•  Bing users spend more time viewing results above the fold. On Bing, users spent around 9.8 seconds compared to 7.8 on Google.
• Bing users took longer to view the first organic result. On Google, users viewed it after 3.3 seconds. On Bing this was 8.8 seconds.

In summary

I’d recommend reading the full article for more detail around the tests, but there are some interesting findings.

It seems that the f-shaped pattern may be no more, though I’d like to see other eye tracking studies before drawing that conclusion with certainty. There are so many variables – number of ads in results, images, featured snippets etc – that can effect the reading pattern.

There may well be a number of different patterns according to result types and, of course, user behaviour may change according to the intent behind the search.

One thing seems to be clear though – the top two or three results still command most attention. (This is from an Advanced Web Ranking CTR study in 2014)

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RLSA and Customer Match: using smart segmentation for big wins

So we all know about RLSA (retargeted lists for search ads) and its ability to use Customer Match, but how many of us are actually taking advantage of it?

The big problem with RLSA Customer Match is that in order for it to really have an impact on volume and performance, you need to have a very large customer list.

To be specific, leveraging RLSA with Customer Match is only worth the effort if you have a list of customers larger than 50,000.

So let’s say you do have that size database. How do you actually use RLSA with Customer Match to make the most of your re-engagement efforts? It all starts with segmentation.

We’ll go into how to do that, then explain why creating a campaign for each segment is important (TL;DR: it allows you to customize messaging and landing pages).

Segment your audience

The first step is to smartly segment out your customer list. There are a couple of ways to do so:

1. Use Average Order Value: Segmenting out audiences by high AOV, mid AOV, and low AOV helps determine which audiences tend to purchase our more expensive, luxury/premium type products and those who go after the cheaper items.
2. Use gender-specific categories: If your customers have purchased men’s clothing, accessories, or products or women’s clothing, accessories, or products, make sure your segments reflect that.
3. Segment by brands/line of product: If you have certain types of brands or lines of products, you may want to segment customers out by the brand/product line they’ve purchased.

Now that you’ve segmented your customers, you can create an RLSA campaign for each audience segmentation. Take the AOV example above. Based on that segmentation, you would create three campaigns: RLSA_HighAOV, RLSA_MidAOV, RLSA_LowAOV.

Split out segmented campaigns to get creative and destination control

Everyone knows that RLSA reaches users with high intent, which means that higher bids are appropriate; you can do that by just layering RLSA on existing campaigns and applying bid modifiers.

So why go through the hassle of creating additional campaigns for RLSA efforts?

Well, the benefit of creating them in separate campaigns is achieving complete control over creative and the post-click experience – getting the ability to tailor creative to each segment you’d like to reach.

As an example, you know that high-AOV audiences performing a relevant keyword search have purchased more luxury products, so your messaging should be more geared around quality, design, or high-end products.

On the flip side, for a lower-AOV segment, you should consider messaging more around deals, discounts, and affordability.

So you have a more tailored creative experience for each audience segment. That’s great – this can help with bringing customers back onto your site. Now it’s time to also ensure you’re sending users in each segment to the most relevant page possible.

Again, taking the AOV example, you would want to send your higher-AOV audience to a page that shows the relevant product/category they are searching for (if you have multiple pages that fit the bill, send them to the page showing more high-end items).

For lower-AOV audiences, use a relevant product page with deals and discounts – or even direct them to a sale/clearance page.

If you have a large customer list, RLSA with Customer Match is a powerful re-engagement tool – but success starts with smart segmentation.

Good luck!

Sana Ansari is the General Manager of 3Q Accelerate.

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Five brief but helpful tips for Google AdSense placement

AdSense is an advertising service provided by Google that gives webmasters a free and relatively simple way of earning money through display advertising on their site.

Of course the terrain of display advertising in the last few years has become a rocky place. With more and more people subconsciously becoming used to ignoring display and the rise of other content-led marketing methods.

However, display ads can theoretically bring in revenue if they are targeted properly and are relevant to the user, context and device.

And now that 21% of internet users globally only use their smartphone to access the internet, spurring Google to strengthen its mobile-friendly algorithm, it’s critical for all businesses to optimise their advertising for mobile.

AdSense has recently issued its own report on tips for mobile web success, and in among the general advice and lovely graphics, there are some brief tips for ad placement that you may not be aware of, so let’s take a quick look at them now.

Mobile ad placement best practice

As the report says, you should focus on creating “a flow between your content and the ad placements.” Basically your ads should feel like part of the user experience, and served when your visitors are most receptive.

The following tips are taken directly from the report…

Tip #1

When using enhanced features in text ads, decrease accidental clicks by moving the ad units a minimum of 150 pixels away from content.

Tip #2

Think about peeking your ad units above the fold for a great UX while maximizing revenue potential.

Tip #3

Potential eCPMs increase when you swap 320×50 for 320×100 ad units.

Tip #4

Anchor social links to make sharing easy.

Tip #5

Use the 300×250 ad unit for a potential increase in fill rates and eCPM.

Of course all these tips merely apply to AdSense display ads. There are many more pitfalls to be aware of when using other ad formats, especially if you use full-screen app ads on mobile sites, which you will be punished for.

And much of this is moot if you don’t have the fundamentals of mobile optimisation correct in the first place.

So your site needs to be responsive or adaptive to every screen size, the page speed needs to be fast, content should be easy to read… in fact, you should definitely read our comprehensive guide to mobile optimisation for more details.

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