Seven Pain Points in Analytics, Seven Possible Solutions

New York, NY (PRWEB) December 03, 2013

Everybody is talking about how data, if used correctly, can deliver greater efficiency and a better customer experience. But achieving this in a rapidly changing environment is anything but easy. From keeping on top of big trends (think the rise of meta-search, holiday rentals and homestays) to skilling up and spending in the right place, analytics teams must be statistically minded and strategically focused. Ahead of EyeforTravels upcoming Smart Travel Analytics North America 2014 show ( which will take place in New York next year, we hear some tips, as well as some of the trends and challenges that are shaping this important travel niche.

1. Meta-search: threat or opportunity?

Pricelines acquisition of Kayak, Expedias of Trivago and then its later investment into Room 77, all point to a growing trend towards meta-search, says Bill Beckler, former head of innovation at Travelocity and and now the founder of a new website For the super-optimiser group of customers – those that spend multiple days looking at dozens of different options, this presents a huge opportunity, says Beckler.

For example, suppliers and online travel agents can now look to measure how users are comparison shopping and reading reviews on meta-search sites before coming to the brands own site to book directly.

For Googles Travel Industry Manager Michael Librizzi, an analytics team may, for example, find that meta-search is very powerful in assisting consumer research and booking. However, just because meta is becoming an increasingly global and meaningful source of traffic for partners in the industry, an analytics team probably doesnt need to adjust their overall strategy. Rather they can incorporate meta into their model like any other traffic source, he says. Ultimately, teams need to ask: how is meta driving last-click bookings and how is meta assisting in bookings?

In terms of direct impact, today meta-search mostly affects B2C companies. However, as B2B companies like Carlson Wagonlit Travel (CWT) look to become more consumer-oriented, it is something this company increasingly expects to come across. I think it [meta] represents a great opportunity, as it allows analytics teams access to more content, explains Catalin Ciobanu, Director, Global Product nnovation at CWT. However, this does come with challenges, as the increased amount of content requires more analysis, which can have an impact on the real-time response that is desired in todays world.

2. Technology spend: in house or outsourced?

One of the biggest challenges facing analytics teams is how to maximise their budgets so that any investment delivers greater profitability. For OTAs like, Expedia and Travelocity, Google is the biggest drain on a budget. Most of these guys spend more on Google than on their own travel technology, says Beckler. And in many cases this technology piece is outsourced to agencies. As head of innovation at, Beckler quickly learnt that agencies dont live or die based on travel trends or for tweaking data and integrating a Google strategy with other technologies or information from elsewhere.

Recognising this, he helped to bring the paid search team in house. As a result, Beckler says the firm was able to squeeze out a lot more value from the money we spent on Google.

If you are in any doubt about whether to invest in analytics, take note. While at, Beckler helped to grow the in house analytics team from five people to 30. As a result, the company was able to make substantial savings on the back of a multi-million dollar investment.

3. People Power: skills dont come cheap and are hard to come by.

Speaking of investing in people, both Ciobanu and Beckler argue that one of the biggest pain points in analytics is finding the right people. The wide variety of skills required including an understanding of maths and statistics, the ability to write code on a daily basis, sound business sense and strong communications skills, are a complex combination. It can be tricky to find the person with the right mix, says Ciobanu.

In addition, people with the right skills are often really expensive as their skills are very much in demand in the financial sector, which has higher margins and can pay more. Starting salaries for good predictive modelling people in financial services can start at around

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