Universal Analytics & Single User View
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Understand who your visitors are, what happens after they convert, what they do in the future, and how much money they make you - and use this to influence your keyword research, strategies and tactics.
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Universal Analytics & Single User View
- 1. Universal Analytics & Single User View @jonoalderson
- 3. Who doesn’t love keyword research? @jonoalderson
- 4. Who’s seen this chart? @jonoalderson
- 6. So what can we do? @jonoalderson
- 8. Challenges • Device proliferation • Defining cookie & session behaviour • Issues with non-linear content consumption (channel hopping & tabbed browsing) @jonoalderson
- 9. Single Visitor View Keyword 1 Keyword 2 Keyword 3 Bad decisions! @jonoalderson
- 10. The real power of Universal Analytics @jonoalderson
- 11. Making this happen: Identifying a user Browser fingerprinting (Pantoclick[sp?]) @jonoalderson
- 12. Making this happen. 1. Get and set the user ID (however you go about getting it) 2. When users complete actions, extract GA data from the GA cookie (ID, campaign parameters, custom dimensions*) and pass downstream to CRM/systems 3. When stuff happens in these systems/places (e.g., sales), pass that info back to GA along with the ID 4. Profit *Avoid PII! @jonoalderson
- 13. Go downstream • Offline sales • Phone calls. App usage. Account preferences. Billing methods. • Intermediary actions; Likes, shares, downloads, etc. Microconversions! • Changes / up-sells / cancellations; go long! @jonoalderson
- 14. If you’ve no mechanism for collecting user ID… @jonoalderson
- 15. This is now the real world @jonoalderson
- 16. Thinking outside the box • Which terms generate multiple conversions over time? • How do multi-device visitors behave, and where should your focus be? • What about… • Which terms have a higher propensity to be used by people who have children? • Which terms contribute more when it’s rained in the last three days? • How do people who travel a lot consume content, and how does this affect conversion? @jonoalderson
- 17. One last challenge… • Everybody’s website is unique. • Everybody’s business is unique. • Every brand’s real-world technology and digital infrastructure is different • There’s no escaping that this needs bespoke development • …But so few people are doing this at the moment, that it’s worth tackling the hurdles. @jonoalderson
- 18. Who’d like to get really technical? Pro challenge: Use a Server-Side Data Layer @jonoalderson
- 19. Resources • UA implementation https://developers.google.com/analytics/devguides/collection/analyticsjs/ • “3 cool analytics hacks” http://bit.ly/ua-hacks • “Using Universal Analytics To Segment By Weather” http://bit.ly/ua_weather • Extract ‘classic’ GA campaign data from cookie; JS example http://bit.ly/extract-ga • Use-case support or exploration Talk to me afterwards! @jonoalderson
Editor's Notes
- GA centricity?
- We have loads of data.=====The legacy of our industry means that we need to work doubly hard to model and prove ROI.Modern SEO, which requires so much investment in content, customer service, and real value propositions – which the organisations we work with or for will often struggle with – requires huge buy in… which needs a business case.We need data to show that the voodoo that we practice – whether it’s the mysterious world of link building, or something resembling post-modern digital PR – makes a difference in the real world. That’s how we unlock budget, enlighten HIPPOS, and make a difference in the world.Except the data we use is comprehensively and fundamentally flawed. Much of it is simply ‘wrong’…. and we’re making bad decisions.Thankfully, we have some new toys which can help us fix that.
- A starting point for most strategies….Keyword research is important, but flawed. We base many of our tactics on the market size, competitiveness, and opportunity – and this process, or one like it, is what drives that.Using PPC data, offline influence, seasonality, personas, buying cycles, other channel influence... Overlap with competitorModel trends, forecast performance, even account for data availability or clarity issues like ios6 or keyword not provided... Estimated traffic/conversions, in line with strategyIt's sophisticated, strategic yet reactive, and provides a roadmap for a long-term content marketing strategy. This is a big piece of work, and it becomes gospel. But we're blinded by our vision of the truth.
- Models where the market opportunity generally is in any vertical, based on the way in which people search. This is one of (many of) the primary determining factors of many SEO strategies; one of the first steps. ‘Long tail content strategies’This is evil, too.=====This is overly simplistic, and reinforces our visitor=keywordview of the world. This visitor with this keyword is different from that visitor with that keyword.It implies that you have to choose. That there are different audiences which need different strategies or tactics. Different people who search in different ways. Many people fitmultiple points in a single relationship, over time.What happens if I hit both, a month apart? What happens if I hit all of those touch-points in an hour whilst researching price/proposition/product? What happens if I change channel three times in a single Google Analytics session, and convert on a visit from an un-tagged email campaign?What does my keyword research tell me then, about what works, what doesn’t, and what I should be spending my time and money focusing on?
- As the industry matures, we’re all hearing a lot about attribution modelling and multi-touch attribution. Attribution modelling.====We all absolutely need to be thinking about multiple visits. Success metrics and KPIs which look at visit-level outcomes. Propensities to convert and weighted time decay channel contributions where SEO isn’t necessarily the last click (or even the first click). Where we still to think in terms of fractions of conversions because all we care about is overall contribution to success. Amazing. There’s a dreamy vision for you.But it’s a bitch to factor all of this into keyword research. Fire up Excel power pivots, make some coffee while it loads, buy some more RAM because it’s still not loaded, make some more coffee, take some codeine for your migraine, then give up because the interface is a nightmare and it’s eaten your hard-drive and melted your laptop.We need this stuff if we’re going to make good decisions, but most of us can’t, realistically or practically, factor this kind of scale of maths & calculation into research phases and keyword data. Not if we want to be quick, clever, and successful.
- I really like this picture. Where do you buy figurines of pensive little businessmen? Amazing.===So. This is scary, but we manage. We make good decisions, even with our flawed view. But we can do better, without having to make it an insurmountable challengeThe big underlying challenge here is that we want our strategies, planning and tactics to impact the bottom line; and often that means going beyond web conversions into ‘real world’ data. How do we understand that keyword X, or tactic Y = £££?Online driving offline, things like product returns, drop-offs from web conversion to actual sale, lifetime value calculations, service/subscription-based models with recurring fees. All need considering.
- Ecommerce store.Techie/geeky products. Male-centric branding, marketing, advertising.Lots of SEO, high performance, all good.DID THE RESEARCH.Except it was mostly women buying gifts for their partners.Different psychology. Page titles. Lower rankings, higher click-through, higher conversion. Good went to Great.Sophisticated!Need to understand what performance really looks like. But this level of integration is complex.
- Step one:We need to tie together multiple visits, over multiple devices. This is one person.===Doesn’t matter if the third visit happens a year after the second, and if the first two happened within minutes. One visitor.Blah blahblah. Everybody’s talking about this like. Go play with Universal Analytics, read the documentation, get an account in place and run it in parallel. Use Google Tag Manager, too, if you don’t have a tag management solution.
- This is more exciting than it looks!=====Understand what happened after they ’converted’, and pull that data back into Google Analytics.; applied to keywords, pages, segments, everything.Boom.Offline sales.On-going revenue (lifetime value!).Returns & cancellations.Real monetary outcomes. In your VPV and ROI calculations. Wow.
- Get social…===All have APIs which allow ‘sign in via...’ or ‘register for our app’; even if the ‘app’ is just the site (sign in with Facebook).Every time they visit your site, when they’re also logged into that network, you’ll know it’s them.Find a way to justify getting a network sign-in. Make a game. Or a widget. Or use oAuth.Grab it, associate it, and you can use it forevery action you can tie back to that user.
- Passing data back and forth, and applying retrospectively.Boom.Offline sales.On-going revenue (lifetime value!).Returns & cancellations.Real monetary outcomes. Right back to landing pages, territories, and standard reports.
- Then you’ve some big challenges.===Not enough to be just brochureware or info; in the era of content marketing, and the cost of not engaging with users in a way which makes them want to talk to you is that you’ll miss out on all of this, whilst your competitors take advantage. ZMOT – usually used to evangelise content marketing. Applies here, too. “the age of asynchronous brand communication is dead”.Nurture funnels. Hearts and minds.Bigger challenges.But use this as part of your rationale to make changes. For brands and organisations who really struggle to ‘get’ good content marketing and SEO, where you’re struggling to get buy-in, this might be a better attack vector.
- Propensity to become a repeat-buyer.Propensity to be up-soldBad leads, which have a higher-than-average dropouts between enquiry and salePropensity to recommend to a friend and for that friend to go on to be a customer. Or for that friend to become a higher-than-average spending customer. Or to subsequently recommend.People who engage, create UGC, share and evangelise, but don’t spend
- WHAT’S A NORMAL DATA LAYER?Data layers typically client-side. Dump vars to source code.Server-side = new with UA. You can use lots of clever logic. Calculate things.“This person has visited more than X pages in Y section”“This person is scored as a valuable lead”“This person have performed both X action and Y action, been exposed to this banner, and it’s a full moon”Count things, use triggers!Join up significant actions, trends, scenarios; pass through to CRM, pass back to GA to tie back to keywords. Adjust targeting and tactics.