The democratisation of analytics is upon us and will help marketers to make better decisions. Ritesh Gupta finds out how
To gain competitive advantage, travel companies have been refining their approach to data management. Every part of this process from data access to integration, quality, and governance requires focus in order to ensure a strong foundation for making use of data from different sources. Such initiatives can contribute to both analytical applications such as business intelligence, data mining, text analytics and operational ones including CRM systems. Marketers acknowledge that predictive models as well as core data must be capitalised on and wherever possible used to maximise performance in support of outbound and inbound marketing efforts.
Recent developments, such as improvements in data visualisation technology have shifted how marketers make decisions. Today it’s less about gut instinct and more about analysis. The proliferation of devices, channels and sensors has caused us to generate more data than ever before. The advent of the data storage-and-retrieval freeware has also played its part.
In search of operational excellence
Analytics is increasingly helping marketers to understand key aspects of attribution – mapping out how conversions overlap across multiple online channels and also in understanding how the combination of media influences latency or quicker conversion. It is, therefore, lending a new dimension to making every dollar count.
Google Analytics attribution methodology, which is still in beta testing with premium customers, is specifically targeted towards channel interaction effects. They look at all site visitors who arrived via e-mail click, then SEM click, then URL direct type-in and observe that particular group’s rate of conversion. Then it is compared to the conversion rate of visitors who came in via e-mail and then DTI (Direct Type In, the channel which represents a site visitor arriving on your site by typing its URL directly into the browser window) with no SEM involvement. The conversion delta between these two groups should represent the impact of SEM on conversion. “If they find that SEM has little impact, that could be a painful internal conversation,” explains Jonathan Isernhagen, Director, Marketing analysis, Travelocity.
Spotlight on digital analytics capability
Suppliers and intermediaries are keenly looking at emerging capabilities for analysing web and mobile behaviour, with respect to predictive analytics, data mining, and forecasting.
Suneel Grover, Senior Solutions Architect, SAS, says one capability that is worth exploring is ‘hyper-focused’ on search marketing.
Grover breaks it down by asking the following business-led questions. What if we increase our paid search ad budget by 10%, 20% or 30% in the next two weeks? How will each of those scenarios impact overall website traffic?
“This touches on the ability to accurately predict what website visitation will look like in the future based on certain scenarios. In business and visual analytics, this is known as forecasting, and scenario analysis. The unique twist is applying this set of analytic techniques to a digital marketing challenge,” says Grover.
Assuming that your organisation owns the digital behaviour stream that captures your website’s traffic behaviour, this data can be fed into a forecasting model to first predict what will happen in the future. Marketers can see how overall site traffic might increase or decrease at varying velocities – by week, day, or hour – all wrapped up in a 95% upper and lower confidence interval to highlight the most likely, best and worst case scenarios. Given this information marketing leaders, who have a desire to maximise their website’s visitation naturally, will wonder what will happen if they allocate more ad dollars to one channel (paid search) versus another (email). Will this, for example, make a difference in predicted traffic patterns?
The answer, of course, is: it depends. By using scenario analysis in conjunction with forecasting, marketing analysts can easily inflate the potential impact of a 10%, 20% or 30% increase in paid search traffic, and then view how this will modify the forecasted prediction of overall site visitation.
Takeaways could be:
- A 10% increase in paid search visitors would provide a 13% increase in overall site traffic in the forecasted time period (incremental 3% lift)
- A 20% increase in paid search visitors would provide a 28% increase in overall site traffic in the forecasted time period (incremental 8% lift)
- A 30% increase in paid search visitors would provide a 56% increase in overall site traffic in the forecasted time period (incremental 26% lift)
”As you can see, adding a little bit more into one digital channel can have varying, and sometimes, dramatic changes in overall digital traffic,” says Grover, so now people might wonder how difficult it is to perform these types of analyses. “I’ll be honest – the emergence of visual analytics in the data visualisation technology space makes leveraging these approaches much easier to achieve. We are living in a time where analytics is not just for a select few.”
The opportunity is too large, and the democratisation of analytics has begun. The industry is only expected to get better with such scenario planning and marketing mix optimisation.
Jonathan Isernhagen, director, marketing analysis, Travelocity is scheduled to speak at the forthcoming Smart Travel Analytics North America 2014 conference, slated to take place in New York City (February 11-12).