There have been technology and behaviour changes in Analytics in 2014. In this article, our Analytics guy Shaun runs through how medium companies are leveraging data for a competitive advantage. Price and functionality improvements are fuelling this exciting time.

We have seen the widespread adoption of A/B testing in large companies, with medium companies starting to make the move to incremental data driven changes through A/B testing as well. For web insights, new features in Google Analytics include Universal Analytics and Enhanced Ecommerce, and more recently Demographic and Interest Segmenting, has meant greatly increased insights into behavioural difference between different website users. So many changes in a market can be hard to grapple, and many businesses just don’t adapt at all. To ensure you remain competitive you must make a measured move to keep your marketing budget accountable, and new analytics insights now allows you to do just that.

The best business decisions are always driven by data; data that is readily available, and data that is gathered specifically for that decision. Unfortunately, this mindset hasn’t always extended into marketing decisions as much of the data wasn’t available; this is no longer the case. The most significant change in 2014 is the advent of the ability of marketers to measure – almost exactly – how many sales have been made due to each and every campaign. You are no longer restricted to previously immeasurable success metrics such as ‘brand awareness’, ‘reach’, or ‘impressions’. With the new tools at our command, we need to crack down on how these and other marketing activities account for the bottom line. To do this, however, we need to wade through all available data to find those that help to inform decisions and measure performance.

At the end of the day, you can have all the data in the world, but if you can’t or worse don’t – do anything with it, then there is no point in collecting it in the first place. Data in marketing, just as with all data, needs to be used to inform decisions relating to business objectives. It is all too common for businesses to fail into the trap of feeling that the data is more easily available is the data that matters. Think about Facebook post reach, the number of likes, and the number of shares. I get as warm and fuzzy as the next person when I get public recognition, but if it doesn’t bring you more sales, either now or in the futures, then this data is not informative for business goals. There are many example of this, you are probably thinking of other data you check every week or so. For this reason, it is important to focus on the end goal data; sales data.

“Likes are for Vanity, Sales are for Sanity”

Segmenting audiences and demographic information. User segment insights have received a significant upgrade this year. Looking at groups of users according to behaviour such as a threshold of time on site, or users who make a purchase, and demographic insights – such as gender, age or interest group – grants you better insights into different target audiences. The Google display network of ads has now been able to leverage its data to approximate the demographic information of approximately 60% of users. This means that you can identify the differences in behaviour between men and women, over 45s and under 25s, and android users compared to iOs users and many other details, and of any combination. From what we have seen so far there are very often significant differences in behaviour between different groups. The significance that this has is really quite remarkable for business decisions, and to inform changes to your web strategy. It is not uncommon for a particular demographic to have significantly different purchase behaviour. This means that you can increase your advertising activities where you are able to target these demographics specifically and bid more for more profitable segments.

So how have the changes this year contributed to this data collection, the data used to make decisions or measure performance? Universal Analytics was a change introduced early this year to Google Analytics while providing extra insights on the default set-up, the strength was in the opened applications of the code that is now available. With developers’ help, data from Google Analytics can now be imported into your CRM, and custom user attributes from our CRM can be sent back into Google Analytics. Users can now be tracked more successfully across multiple devices if the site has a sign-feature, which increases accuracy of data in an increasingly multi-screen environment. The real power of custom applications of Universal Analytics is yet to be seen; there are some exciting developments expected in Universal Analytics.

Enhanced Ecommerce was a major add-on for anyone who has a dollar value transaction on his or her site. Once set-up with your product data feeds, Enhanced Ecommerce allows you to view, from the Google Analytics interface, data relating to purchases at the product and value level. What this means for business decisions is that you can identify the behaviour of groups of users who purchase specific products, or whose order value is within a certain range. With this infromation, you can really drill down into the best savings that can be made in your marketing.  A company may notice that a certain demographic is much more likely to purchase certain product combinations, or have a higher order value. This information can be used to improve the web experience for these users, and can be fed into the bidding strategies for advertising to these specific audiences.

While not a new feature, building AdWords audiences through Analytics deserves a mention. Google Analytics can create a segment of users who fit a certain criteria. These segments can be exported directly into AdWords and can be targeted through some advertising networks. You can use this information in two instances of your advertising activities. The first application is to increase the effectiveness of remarketing. Remarketing is typically used to show display ads to past visitors of the site, but with advanced segmentation, you can instead just show display ads to those in segments based on behaviour or demographics. Instead of showing display ads to all past user, you can choose only those who were most engaged with the site. Secondly, you can use the information in conversions of market segments to target the broader audience of people within this category – thus increasing the effectiveness and viability of display advertising. Audience building is now much more powerful with the additions of Ecommerce, Universal Analytics, and Demographics data. We can now target audiences that are of certain demographic groups, or who looked at high priced items for specific advertising campaigns. You can segment Analytics data by these segments – furthermore, all of these groups can be targeted either with remarketing, or even in general from AdWords:

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Demographic Information


  • (Male/Female)

Age Groups

  • 25 – 34
  • 35 – 44
  • 45 – 54
  • 55 -64
  • 65+

Geographic Information

Location down to the state and mojor city

Affinity Categories

  • Movie Lovers
  • Technofiles
  • TV files
  • Travel Buffs
  • Shoppers/Shopaholics

In-Market Segments

  • Employment
  • Real Estate
  • Financial Services
  • Travel
  • Apparel and Accessories
  • Home garden and furnishings
  • Automotive
  • Consumer Electronics etc

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