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Personalisation & Measurement

Personalisation & Measurement



An overview of introduction to, and overview of, personalisation and measurement.

An overview of introduction to, and overview of, personalisation and measurement.



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  • The web allows us to access/generates dataThis data IF USED CORRECTLY can provide insightsThese insights can help us to improve efficiency, process and deliver a better ROI
  • Mid-1990’s: ATG/Broadvision early productsA means of enhancing the visitor experience to a website by elevating certain functionalitiesAmazon, eBay: early pioneers
  • 52% of digital marketers agree that “the ability to personalise content is fundamental to their online strategy”41% committed to providing personalised web experience
  • What is the impact of personalisation on ROI & how is it measured?50% use “time spent on site” to measure increased engagementONLY 32% say their CMS enables personalisation YET 37% are targeting personalised content in real time33% say they use data effectively to maximise conversions27% test to see how different personalisation performsAND...6% use social graph data to personalise content42% say they can personalise using anonymous data
  • Fall in the cost of deploymentMany mid-tier CMS solutions incorporated this functionality as a USP to set themselves apartMORE CONTENT, so companies need to work harder to point users to the RIGHT content
  • A standard site presents the same content to all users, regardless of profile, preferences and behaviour.A personalised site is one where the experience is changed to be different to each user based on a number of pre-defined factorsPersonalised sites are PUSH- oriented, non-personalised sites are PULL- oriented
  • (1) EXPLICIT: based on the user’s PROFILE, and can be PASSIVE (allowing users to make choices as to what they'd like to see) or SEGMENTED (allocating content choices based on a logic layer applied to that profile)Examples: Pros & cons
  • (2) IMPLICIT/”BEHAVIOURAL TRACKING”: based upon a user’s clicking activity, the site dynamically offers content based upon that activityExamples: AmazonPros & cons
  • (3) HYBRID: a solution that is designed to offer the best of both worldsExamples: eBayPros & cons
  • (4) ADAPTIVE: where incremental website user behaviour monitored and personalisation takes place automatically Watch this space – tech developingAmazon? Google?
  • The rise of mobileGrowth of behavioural targeting“Big Data”: larger data sets to improve personalisation, esp., in recommendations/promotionsBroader shift to cloud/SaaS tech: user behaviour even more critical to the underlying tech intelligence of these systems
  • Here to stay and it will only increase in use and adoptionThose already using it will improve their systems, as evidenced by the increase in ROI that results from enhanced personalisation techniquesThe rise in personalisation part of a broader paradigm shift in tech landscape involving mobile-first, responsive & adaptive design, and cloud computing
  • QUANTITATIVE measurement: tells you WHAT is happeningQUALITATIVE measurement: tells you WHY it is happeningBOTH are important
  • Log files Taggingmore advanced analytics, ubiquity of Google Analytics bespoke CMS systems
  • Who is using my site?Where are they coming from?What content are they consuming?How are they engaging with that content?What can we do to make their experience better?
  • There are no independently meaningful metricsAnything can be a source of dataThe truth lies in the context...
  • Traditionally, the top 4 metrics worth looking at are likely to be:Traffic sourcesTop contentBounce rateGoals/conversionsOnly meaningful when they are interconnected:In this example, always evaluate (i) traffic sources and (ii) top content in light of (iii) bounce rate and (iv) conversions
  • Big Data to harness business intelligenceMore data sourcesMore platforms (particularly mobile: tablet, smartphone)Social media – also a source of contentionGoogle Analytics & “Universal” analytics
  • Universal analytics: users can tailor it to their needs, integrate their own datasets and get a better view of the entire marketing funnelAttribution Modelling Tool: build models that give credit to all their digital channels, provide insight into the impact of various marketing programsCost Data Import: import users’ cost data from any digital sourceCustomer Lifetime ValueRecency, Frequency and Monetary ValueCustom Dimensions/Metrics: widen dimensions for bespoke measurementMobile
  • The most important data point: how customers/visitors interact with your web presence:Usability testing“Follow Me Homes”A/B TestingSurveyingAn ongoing process...
  • As personalisation becomes more ubiquitous and sophisticated, so there is an increasing need for a real-time, instantaneous customer analytics capabilityAs with the broader analytics scene, where personalisation is present it is vital to understand the data generated by analytics tools. Good analysis of data is imperative.
  • Web measurement tools need to be understood contextually to derive the most benefitThese tools are increasing in sophistication to match both technological advances and also heightened business expectationsThe landscape for measurement is increasingly fragmented and diverseAll of these factors highlight a need for more integration, as increasingly disparate data sources & graphs, coupled with a fragmentation of platforms/devices used results in deeper challenges for measurementAs ever, the availability of more advanced analytics correlates with a need to have a more advanced & nuanced understanding of the analytics tools at our disposalPersonalisation amplifies all of the above factors, and creates a virtuous loop

Personalisation & Measurement Personalisation & Measurement Presentation Transcript