With so many search signals, how do you keep up?

Search behaviour has changed dramatically since Google launched 18 years ago. There are now over 1 billion users,[1] who make trillions of searches each year.[2] Today these searches are much more complex than they were at the beginning—people are asking more and more and expecting better answers in return. 

What hasn’t changed is that search is the best indicator of what people want. If you look back at your own search history, it tells a story of your interests, desires and needs. In the moments of your day when you have a question to answer, search is the tool that answers the question.

The rise of smartphone ownership and usage has multiplied these moments. Now when people need to find information, they can do it then and there. The moment someone sees a product they want, they can pull out their phone and search for it. This means how people purchase is more complex. On average, people who use multiple devices to research their purchase have 7.6 touch points in their journeys compared to 3.5 touch points for those who researched only on their computers.[3] And people are doing this in great numbers—64% of people buying laptops use their mobile to research the purchase. Even in categories like skincare or car insurance, over 40% of purchasers are using their mobiles to research.[4]

Traditionally marketers have had to rely on demographic signals like age and gender to ‘guess’ who might be interested in their brand or category. But demographics rarely tell the whole story. For example, (if we use stereotypes) we might assume that the majority of DIY and sporting goods enthusiasts are men, or that video game players are teenage boys. But search reveals a different story: on mobile, 56% of sporting goods searches and 45% of home improvement searches are from women, while only 31% of video game searches on mobile are made by men aged 18 to 34.[5]

In a similar vein, businesses in the past would know the search term that a customer had used, but now they have much more information: the location of a searcher, the time of day, which devices were used and—if they’ve been using their data wisely—the customer’s past shopping behaviour. This gives them a huge opportunity. 

A good example of a business using these new signals is Turkey’s low-cost carrier Pegasus Airlines, one of the first to use Google Customer Match. Customer Match allows advertisers to upload lists of customers’ email addresses from their own CRM systems to create and target custom audiences based on those lists. 

●      To increase ticket sales and decrease costs, Pegasus and performance agency Hype used first-party data and Google Customer Match to categorise search users into three groups: members of the Pegasus Plus Mileage program, former customers, and users who had previously contacted Pegasus without buying tickets.

●      When any of these consumers searched for queries like ‘flight’ or ‘flight tickets’, Pegasus Airlines was able to customise its bids and ad creatives. Compared to standard search campaigns with similar targeting, Customer Match enabled:

○      32% higher click-through rate

○      12% more revenue per conversion

○      13% lower cost per acquisition

While Pegasus Airlines provides an example of data being used intelligently, consider all of the data that businesses are not using. Many find it difficult to look at all of the variables in search terms, locations, times, devices and past behaviour across millions of customers. This proliferation often requires that analysts spend more time looking at the data, which leaves less time to take action on the data. 

At the same time, consumers have become more demanding:

●      52% of people rank relevance as the number one reason they would engage with an ad, and 74% are frustrated when they’re served an ad with no relevance to them[6]

●      29% of smartphone users will immediately switch to another site or app if it doesn’t satisfy their needs[7]

●      40% of online shoppers start their research on a smartphone and make their final purchase on a computer or tablet, while 50% of consumers who conduct a local search on their smartphone visit a store within a day [8]

To help with these challenges, new tools are available for attribution, measurement and automation that can relieve the amount of time spent on reporting and optimising, so time can be spent on more innovative tasks.

For example, many businesses still optimise based on the single interaction that came before a purchase—the last-click model (in the US, 40% of enterprises still go by first-touch/last-touch attribution).[9] The good news is that nearly half of marketers plan to change this approach in the next one to two years.[10] Google’s solution for a single view of the user across browsers, apps and devices for AdWords campaigns is Cross-Device Conversions, which uses aggregated and anonymised data from the huge base of signed-in traffic across Gmail, Chrome, Android, the Google app, and so forth. This allows us to provide advertisers with highly accurate and granular reporting on cross-device behaviour without compromising user privacy. We only show cross-device conversions when we have at least 95% confidence that the calculation is within 10% of the actual value. Advertisers using cross-device conversions see on average 16% more conversions that would otherwise not have been attributed in AdWords when using single-device measurement methods.[11]

Meanwhile, people aren’t just switching between screens—they’re also switching channels. An emerging area of focus is cross-channel measurement to assess the impact of digital behaviours on offline activities. Approximately 85% of commerce still happens in store in the UK, but digital is playing a bigger and bigger role in influencing offline purchase behaviour.[12] To help make sense of these trends, AdWords Store Visits estimates what percentage of users visited a store up to 30 days after a search ad click on Google by counting anonymous store visits from opted-in and anonymised location history data. Google’s mapping technology understands an advertiser’s store location and the shape of that store, then connects Wi-Fi, cell tower and GPS location signals to the maps and tracks time spent in the store. This enables Google advertisers to measure the in-store visits that Google Search ads are driving across mobile, tablet and desktop devices. Retailers that incorporate Store Visits data measure four times more conversions overall and ten times more mobile conversions.[13]

When it comes to optimising search campaigns, making changes to accounts is hugely time consuming if you have to analyse all of the data and then test what to change, evaluate that and then roll it out across a large number of accounts. AdWords and DoubleClick can do this for you with automated bidding. You set a few rules, and the tools help you make the most effective and efficient bid by analysing a rich set of signals in real time, including time of day, operating system, audience lists, browser version, and many more. This allows your ads to appear to the right customers, in the right place, on the right device, at the right time.

So, what does the future hold for search marketers? With increased ability to use search on mobile phones, consumer behaviour is getting more complicated. Mobile has also given businesses more information about their customers, which makes it hard for traditional reporting approaches, and workflows are not able to keep up. To be successful, businesses will find it necessary to switch to more sophisticated measurement, attribution and automation tools to keep pace with consumers’ demands.

[1] Source: Google Q4 2015 Earnings Call

[2] Source: Google Data, August 2012

[3] Source: TNS/Google, Mobile Purchase Journey, 2016

[4] Source: TNS/Google, Mobile Purchase Journey, 2016

[5]Think with Google, ‘Why Consumer Intent is more Powerful than Demographics’, December 2015

[6]MarketingCharts, ‘Consumers want more relevant website experiences’, 2013

[7]Source: Google/Ipsos, Consumers in the Micro Moment, US, 2015

[8] Source: Google/Ipsos, Consumers in the Micro Moment, US, 2015

[9] Forrester, ‘Cross-Channel Attribution is Needed to Drive Marketing Effectiveness’, May 2014, U. S.

[10] ‘Cross-Platform Attribution’, eMarketer, 2015

[11] DoubleClick Leadership Summit: Owning the Moment in a Multiscreen World, June 2015. Link

[12] Centre for Retail Research, UK, 2015. Link

[13] Adwords Blog, April 2015, Link