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Google’s new PPC features are loaded with AI

At Google’s San Francisco marketing conference, held in May, the internet super-corporation made some startling claims about the future of its AdWords tool. Of huge interest to anyone who engages in pay per click campaigns in the UK, the event – named Google Marketing Next – saw a number of innovations added to Google’s current offering. Aimed at larger businesses in the main, their presentation of key new features was certainly designed to be eye-catching, but what of the details which will be of more interest to smaller organisations? Read on to discover the future of pay per click marketing and how artificial intelligence (AI) and machine learning will play an ever greater role.

New Customisation Features Help You Hone In

In the near future, Google will allow e-marketing professionals to perform a query that will let them see who, or what sort of surfer, is accessing their website via a pay per click campaign in AdWords. This means that for the first time it will be possible to tell whether a particular search term is being clicked through on from a genuine customer or perhaps someone simply doing a bit of research. Google’s Director of Audience Products, Bhanu Narasimhan, said that this function will allow for conversion rates for in-market audiences that are improved by ten per cent, on average.

Any in-market search feature is likely to improve the ability to attract specific types of consumer. However, this is not all Google have announced. At the present time, there are just under 500 types of in-market audiences that can be displayed within AdWords. In a further announcement made by Karen Yao, the organisation’s Group Product Manager for Ad Platforms, fully customisable in-market audience will now be possible, too. For example, by adding keywords that might have been used by someone looking for a product or service you sell, it will be possible to customise an in-market audience specifically for them. Thanks to the big data and machine learning offering of Google, this should allow for a much greater targeting of customers, new and old.

Target Your Clients’ Life Events

In the past, life event targeting relied on fairly simple AI, but Google’s Tensorflow processing system has revolutionised it. Getting to grips with would-be consumers who are going through a targetable life event means being able to gain a distinct advantage over competitors.

Whether you market to recent graduates, to people who have just bought a home, or to newlyweds, advertising to people in a more structured and, frankly, intelligent way is now available due to Google’s investment in this fast-moving technology.

Use Attribution Modelling Features to Track Customer Interactions

Google Attribution is already available in AdWords, DoubleClick and Analytics, so what needed to be improved? Basically, the issue with many attribution models is that they are somewhat limited when it comes to reproducing real-world behaviours. People just don’t ‘behave’ online in the way that we assume they might. Nevertheless, thanks to Google’s updated store visit data, better store sales data and a consolidation of data that is easier to read, marketing professionals won’t need to try to use the existing tools in the same way anymore. For example, constantly tweaking models for one-off or seasonal behaviours will be done away with. Due to Google’s machine learning, data-driven models will now cleverly weigh up how each click point in a sales and marketing process contributes to the overall outcome.

In Summary

There are four key points to take away from Google Marketing Next. They are:

1. The growth of artificial intelligence in the way Google will run services like AdWords
2. The increased accent on life event targeting.
3. The ability to customise in-market audiences.
4. The fact that automation is likely to play an ever greater role in e-marketing this year and next.

Therefore, it is going to take even more specialisation and expertise to successfully squeeze the best out of e-marketing campaigns in the future. It looks like another learning curve for agencies and another reason why you shouldn’t attempt to use all these tools yourself!

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