martin-heigan-via-flickr
Statistical Data Analysis

#geekTogether: Data Takeaways

The other week, we at graze.com hosted an inaugural Silicon Valley style knowledge sharing event for data professionals – the #geekTogether. The event was born out of a desire to create a platform for fast growing British companies to share data ‘war stories’ freely and openly.

Getting real value out of data is a difficult nut to crack. A few years ago companies thought that one day they’d be able to get answers from data without knowing the right questions to ask. Today we are more practical and focus a lot more on asking the right questions first.

This explains partly why companies largely agreed that one of the most commercially successful business applications of data has been the ability to set, track and forecast key performance indicators (KPIs). As a very simple example, one would assume that for an online magazine subscription service the number of subscribers would be the most fundamental figure when determining success. But how does the level of engagement – free articles, website views, trial uptake – affect the number of fully paying subscribers in the mid-long term?

The ability to identify, measure and act on these engagement metrics, which inform us about customers’ behaviour and their likelihood to become a fully paying subscriber, is what can drive significant commercial returns. Ultimately, we need to continuously review, adapt and evolve our KPIs - the danger lies in valuing what we measure rather than measuring what we value.

Personalising the customer experience was another prominent and somewhat controversial topic of discussion at the #geekTogether. We all agreed that delivering a truly tailored experience, which leads to greater customer lifetime value, is more than challenging – even the great Amazon would still show us a TV in the recommended products list when we’ve just purchased one (why would we need two TVs?).

Some of the barriers to developing effective personalisation include identifying and asking customers for the relevant data which would help us personalise their experience, building an accurate predictive analytics model which accounts correctly for correlation versus causation effects, quantifying and evaluating the success of such initiatives through A/B tests when large samples may not be available, as well as making an investment case to the rest of the company. While most companies admitted that distributing transactional emails with some degree of personalisation was largely what they had attempted to do, others shared more comprehensive successes and set high industry standards.

Given that our ability to extract intelligence from raw data relies extensively on the technologies available to us, this was another topic that could not have been overlooked by the #geekTogether attendees. The importance of cloud database technologies such as AWS Redshift, critical to supporting intensive data analysis, as well as the reasons why real-time analytics matters have also been addressed in detail. When it comes to data visualisation technologies, companies largely agreed that the benefits of implementing software like Tableau or Birst, both in terms of time and money spent, are likely to dwarf the costs.

For most dynamic and agile companies like us, data is and will continue to be a competitive advantage, playing a very important role in our growth and development. With so much data available, however, companies may simply feel overwhelmed or even get stuck in a stage of ‘analysis-paralysis’. At times we just need to take a step back, look at the bigger picture and ask: what are the questions that we are trying to answer as a business; what data do we have and what data do we need; finally, how can we act on the insights drawn from the data to drive real commercial returns? Being able to answer these questions is a major step towards being able to apply data to our businesses to great effect.

There are a number of barriers between getting the data itself and being able to use it, but when everything comes together, the value effective data use adds to a business is unquestionable. One panellist at the #geekTogether summed it up rather nicely:

“Hidden inside this absolute mountain of data is the right stuff. We just need to identify it, streamline it, and bring in the right expertise to make the most of it.”

 

Mica Vaipan is Head of Data and Business Insight, graze.com

PREVIOUS ARTICLE

« Samsung Pays Its Way into Future of Smart Homes

NEXT ARTICLE

What Are They Worth? Tech Giants by Market Cap »
author_image
IDG Connect

IDG Connect tackles the tech stories that matter to you

  • Mail

Poll

Do you think your smartphone is making you a workaholic?