You may be hearing a lot about the scary word known as “big data.” It’s a buzzword used by many when discussing business analytics; a miracle cure for risk management that can help businesses make decisions with degrees of confidence unlike any they’ve ever seen. Big data is expected to play a part in medical advancement, military operations, and of course, your PPC accounts.
The Business Software Alliance (BSA) estimates that Big Data could have a $15 trillion impact on global GDP by 2030. Considering that in 2016 advertisers spent $79 Billion on Google Adwords, it’s safe to say that impact would be substantial.
Of course, with great power comes great responsibility. Big data is complex, but if handled appropriately it can help you tremendously in your PPC campaigns to maximize ROI.
Not willing to spend on big data? It’s okay, you don’t have to spend any more than you already are. Google and other digital advertising platforms are a treasure trove of data being collected for you. All you need to do is advertise and they will report to you all of the data you can imagine that you can leverage to make smart low-risk decisions to boost your ROI.
What Is Big Data?
Wikipedia describes “big data” as a term that tends to refer to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data, and seldom refers to a particular size of data set. Accuracy in big data may lead to more confident decision making, and better decisions can result in greater operational efficiency and cost reduction, and risk reduction.
One famous example of big data success is that of the Oakland A’s and their general manager Billy Beane, who found a way to let the big data metrics evaluate players to find hidden gems. This took subjectivity out of the equation and translated to a low budget first place team. These efforts helped usher in an era of big data in baseball that continues to this day.
Demographic Targeting in AdWords
Google has developed itself into a large collection of data and developed tools for working with it. It is constantly learning about our online tendencies, such as what web pages we like, what kinds of videos we watch, what sort of content we share, etc. Then it serves us advertisements based upon our interests thanks to the data they store. When advertisers use AdWords, they are tailoring their ads to be shown to those in their target audience using big data and big data management such as Google Analytics.
In 2016, Google rolled out some new features in demographic targeting for search campaigns. Using the audience tab, you can view everything from interests, gender, and age group of the people clicking your ads. Using this information, there are multiple options you can take; you can increase bids for well performing demographics, and/or cut off others by bidding down their demographic. You can even create an entirely separate ad group tailored to this demographic.
Using this data to make decisions takes away the subjectivity that once made digital marketing scary. We can now make decisions based on big data with a greater degree of confidence and be held accountable for not making decisions based off of this data.
Remarketing
The big data train doesn’t stop at demographic targeting. Retargeting would not be possible without the use of mountains of data. Although it is a fairly new feature, it has already proven to be effective and in many cases imperative to many digital marketing plans. Loews Hotels is a prime example highlighted by Google, generating $60,000 from an $800 remarketing campaign.
It is possible for us to create intricate remarketing lists that are as broad or granular as we want using the big data that Google provides. You could potentially create lists that go after all visitors to your site, however in most cases it could be best to target users who show more convertible action, such as abandoning a cart or viewing but not completing a contact form.
You can also leverage your time lag report to fully understand the cycle of your conversion. Do you find that people are coming back 5 days after abandoning their cart to complete a purchase? Set the remarketing campaign to cater to that cycle and keep your product fresh in the consumer’s mind.
Showing their trust in their own system, in 2014 Google rolled out a ‘smart list’ feature for remarketing. Using machine learning and algorithms, Google looks through data to analyze signals such as location, device browser, referer and more on a daily basis. The list is then updated to include users who are the most likely to convert.
In order to set this up, you’ll need to have at least 10,000 daily page views, and 500 monthly transactions. Not working with that kind of volume just yet? You can still utilize smart lists, as Google will look at similar businesses and create your list based on that data. Although it would be best to have your own data, it is worth testing out against other remarketing lists.
https://unsplash.com/@kmuza/ CC0
Big Data For Ecommerce
Because Adwords allows you to create highly targeted campaigns, it is important that they are monitored closely and tested regularly to see what works. This rings true especially for ecommerce brands, as they face many marketing challenges.
Ecommerce companies are often working with low conversion values and thus have very slim profit margins. CPA needs to be low and accounts need to be optimized to target what works. Every dollar counts in this industry, and it is with big data that online retailers can target a specific segment of their market instead of wasting precious dollars on a demographic that doesn’t convert as often. Optimization is the name of the game here.
Ecommerce brands are marketing across the country (and in many cases internationally) on multiple platforms and devices. In 2016, 36.6 million online users in the United States accessed the internet exclusively via mobile devices. This information is even more valuable to online retailers, as it gives us the framework to make an actionable decision based upon where conversions are coming from.
Conclusions
Big Data is a big scary buzz word, but for advertisers there is really nothing to be scared of. As an advertiser, you are trying to reach your most relevant audience to get the most ROI. You can use Big Data to narrowly target users and build highly profitable campaigns by experimenting with the plethora of tools and features that Adwords provides you with.
You are the general manager and your business is the team, and much like the Moneyball Oakland Athletics, you can get out there and create a winner on any budget using Big Data. Now go out there and build a winner!
