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Combining Analytics and User Research,[object Object],Alex Tarling,[object Object],User Experience Consultant,[object Object]
About the session:,[object Object],Why is it good to combine methodologies?,[object Object],Why doesn’t this commonly happen already?,[object Object],Some opportunities to combine analytics and user research…,[object Object],… some case studies and some hints and tips to get started!,[object Object]
Who am I?,[object Object],Freelance user experience consultant,[object Object],12 years experience of design research, UX, information architecture,[object Object],Projects for Intel, BBC, Nokia, Orange, New Look, Blacks, Millets etc,[object Object],http://linkedin.com/in/alextarling,[object Object]
User Experience Research,[object Object],“User experience research is a collection of tools designed to help you find the boundaries of peoples needs and abilities“- Mike Kuniavsky,[object Object]
User Experience Research,[object Object],“User experience research is a collection of tools designed to help you find the boundaries of peoples needs and abilities“- Mike Kuniavsky,[object Object],”The field of user experience, is blessed (or cursed) with a very wide range of research methods“- Christian Rohrer,[object Object]
Web Analytics,[object Object],"Web Analytics is the measurement, collection, analysis and reporting of Internet data for the purposes of understanding and optimizing Web usage.“- The Official WAA Definition of Web Analytics,[object Object]
Why use a combination of methods?,[object Object],”When all you have is a hammer, everything looks like a nail”- Abraham Maslow,[object Object]
Why use a combination of methods?,[object Object],All methods have strengths and weaknesses,[object Object],Combining methods with different attributes allows us to:,[object Object],Triangulate between the strengths of individual methods,[object Object],Mitigate the weaknesses and risks of each,[object Object]
Why are user research and analytics methods not routinely combined?,[object Object],Because user research and analytics are often commissioned and actioned by very different functions in the organisation.,[object Object],Because user research and analytics often happen at different stages in the product cycle.,[object Object],Analytics developed in a context to measure against business-goals, whereas user research is deployed as an aspect of the customer experience.,[object Object]
Attributes of different methods:,[object Object],Observational User Research,[object Object],Primarily qualitative: provides insights about users’ goals, motivations and attitudes,[object Object],We can explore context and opportunities, and what doesn’t happen as well as what does happen,[object Object],But, small sample sizes and high cost means we end up with a snapshot in time, and specific demographics. Lab settings can also be problematic,[object Object],So, observational findings open to challenge / multiple interpretation,[object Object],Web Analytics,[object Object],Quantitative and based in real-world data – talks about what is happening. ,[object Object],Large sample sizes mean high degrees of confidence,[object Object],But, interpretation of behavioural aspects is hard without additional customer insight,[object Object],Where we predefine measures, prior assumptions about meaning and significance can become entrenched,[object Object]
Design of Terminal 5 - Risks of insight research…,[object Object]
Quantitative methods also have down sides...,[object Object],”Not everything that can be counted counts; and not everything that counts can be counted ”- Albert Einstein,[object Object]
We have ‘abandonment’ issues…,[object Object],www.shopsafe.co.uk/news/online-shopping-cart-abandonment-analysed-by-royal-mail/10098,[object Object]
We have ‘abandonment’ issues…,[object Object],www.shopsafe.co.uk/news/online-shopping-cart-abandonment-analysed-by-royal-mail/10098,[object Object],… assumptions about the implications of ‘abandonment’ don’t talk to real-world customer experience…,[object Object]
We have ‘abandonment’ issues…,[object Object],(econsultancy.com/blog),[object Object]
We have ‘abandonment’ issues…,[object Object],= Still missing the opportunity to genuinely explore and design for customer experience!,[object Object]
Opportunity 1:,[object Object],Use customer insight data to inform analytics measures,[object Object],So that analytics reporting genuinely reflects and supports the customer experience, not just the business goals,[object Object]
Opportunity 1: use customer insight data to inform analytics measures,[object Object],Deliver actionable analytics metrics from your customer research insights,[object Object],(because user research and analytics often happen at different stages in the product cycle),[object Object],Broker communication and collaboration across informational silos, and between phases in the product lifecycle,[object Object],(because user research and analytics are often commissioned and actioned by very different depts.),[object Object],How to get started:,[object Object]
Opportunity 2:,[object Object],Use analytics data to drive the user research programme,[object Object]
E-commerce redesign project:,[object Object],Driving the user research programme from analytics data,[object Object]
Opportunity 2: use analytics data to drive the user research programme,[object Object],Just do it! ,[object Object],You can do a lot with even basic levels of analysis,[object Object],Think laterally about the sources of data that are available,[object Object],Commission specific analysis of existing data sources,[object Object],How to get started:,[object Object]
Opportunity 3:,[object Object],Integrate analytics and user research to optimise the user experience throughout the product lifecycle,[object Object]
The Open University ,[object Object],support for new distance learners:,[object Object]
Opportunity 3: Integrate analytics and user research to optimise user experience throughout the product lifecycle,[object Object],Ongoing use of analytics ,[object Object],to discover and target behaviors or interactions for the research programme,[object Object],to ‘evidence’ user research insights,[object Object],Rapid iterations of ‘fast’ user research interventions ,[object Object],Targeted against specific analytics findings,[object Object],to generate insights and use-cases for development,[object Object],Integration means adapting the product lifecycle to support continual innovation,[object Object],‘Launch early and listen’ and agile strategies,[object Object],How to get started:,[object Object]
In summary,[object Object],Opportunity 1: use customer insight data to inform analytics measures,[object Object],Opportunity 2: use analytics data to drive the user research programme,[object Object],Opportunity 3: integrate analytics and user research to optimise user experience throughout the product lifecycle,[object Object],Thanks!,[object Object],Alex.Tarling@gmail.com,[object Object]

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Editor's Notes

  1. The focus on optimisation sets an interesting constraint on the use of web analytics – you can optimise a process to improve efficiency, or reduce errors. But the implication here is that web analytics doesn’t have much to offer the design process, and I think there are significant opportunities.
  2. We are shaped by the tools we use habitually. Its good for us as practioners in a range of disciplines to be able to draw on different disciplines. And with the current generation of tools like google analytics means you don’t have to be a specialist to get depth and value.
  3. London Heathrow Airport Terminal 5 forecast that future travellers would be older. Research into older travellers showed they often go into the toilet, so many new toilets were planned. !However, deeper investigation discovered they were going into the toilets….to hear the announcements. It was the only place they could find where they could clearly hear the flight calls! So now the airport is putting new audio areas where you can clearly hear your flight call…. (credit Clive Grinyer)
  4. Shopping cart abandonment can be easily measured. Shopping cart abandonment is a useful metric from a business perspective – it measures sales not made today. But problems arise when it is used to describe the customer experience – and when conclusions like this one are drawn So abandonment as it is framed here is a technical concept that originates from the mental model that the business has of its process. It doesn’t effectively describe the customer experience, and actually it can serious constrain thinking from a customer-centric perspective.http://www.shopsafe.co.uk/news/online-shopping-cart-abandonment-analysed-by-royal-mail/10098
  5. http://econsultancy.com/blog/6075-checkout-abandonment-on-the-riseSo of course it easy to see that customer behaviors are significantly more complex than the headlines suggest – as per this recent research from Forrester. So 3 out of 5 of these reasons don’t represent abandonment at all – they represent real opportunites to create an ongoing relationship with the customer.
  6. The fact that we continue to use these business-objective metrics to characterise customer behaviour is potentially a real missed opportunity.
  7. Case study for previous iteration of the design: conversion rates had declined over the lifetime of the site – around a 2-year process. The sense was that the shopping basket and checkout were increasingly outdated and this was preventing completion of sales. A project was defined to re-design the checkout and basket and comparative usability study commissioned. Closer exploration of the available analytics didn’t really support the theory that the checkout was the problem area and the user study was widened. It actually turned out that the merchandising strategy for the site had also degraded over the lifecycle – customers just weren’t being presented effectively with product, and the checkout process was not the main issue.
  8. May require additional relationships within the clients
  9. A very challenging target audience of ‘at risk’ learners – older, generally low levels of previous education, generally lack confidence with computers, very often have other issues that are a barrier to engaging with education. A ‘launch early and listen’ strategy. An initial exploration of the analytics helped us define the targets for the research for this iteration, and helped define the demographics – so a very targeted cost-effective piece of user research. One of the main target areas was around use of video on the site. Less than 10% of visitors use the video – so significant pressure to reduce its use on the site. But those that did often watched several video segments. From the user research we identified specific customer segment – the core of our most vulnerable users that were motivated and engaged by video. And a model for what they got from the video and how they were likely to use that defined how to use video in the future.
  10. Analytics isn’t enough – does not generate formative insights on its ownQualitative, observational user research generates formative insights, but is too expensive to do continually