data-driven growth - analytics & attribution for marketers in 2016 | turing festival

📈 🚀Andy Young, 500 Startups / Freelance

Turing Festival 2016

Analytics tools and tips for marketers in 2016

Data-driven Growth

Andy Young - @andyy - http://bit.ly/analytics-turing

Hi, I’m Andy!@andyy

Photo by Dan Taylor - dan@heisenbergmedia.com

Agenda

Why analytics?

Deconstructing the modern analytics stack

Lies, damn lies, and tech metrics.. - analytics in the real world

Andy Young - @andyy - http://bit.ly/analytics-turing 🤔Why analytics?

Don’t start with the data

Common Analytics FAILS• Drowning in data

• Not identifying key questions to answer

• Not starting withclear hypotheses

Common Analytics FAILS• Drowning in data

• Not identifying key questions to answer

• Not starting withclear hypotheses

We need to know how we’re doing

• Overall business/product • Individual experiments, campaigns, channels, customer segments

• What is working? • What is not? • Where to focus for improvement?

Analytics Pros..

• Start with a hypothesis • Identify, collect + analyse necessary relevant data • Conclude & action • Iterate, revise

Analytics for Growth📈

Growth?

•More users

•More revenue

Analytics techniques• Early stage:

- innovation accounting (Lean Startup)- cohort analysis

Analytics techniques• Early stage:

- innovation accounting (Lean Startup)- cohort analysis

• Growth stage: - growth accounting- customer segmentation- channel analysis - funnel economics

Early stage questions

Are we getting traction?

“Traction is the rate

at which monetizable value

is extracted from customers”

Innovation accounting?

Cohort analysis?

Growth stage questions

Are we growing?

Growth Accounting

Are we growing?

Growth Accounting

👌👉 http://bit.ly/social-capital-growth-accounting

Funnel performance?

As marketers we need to understand

the full funnel

Growth stage

Which channels bring the most customers?

Which channels bring the best customers?

How much do we want to pay per click?

..as much as possible?!

Outspend competitors

Activate new channels

Customer segmentation & channel performance

For different groups of customers:

• Where do they come from?

• How do they behave?

Customer segmentationUsers acquired via different channels

will have different behaviours

Different cohorts will have different experiences of your product

Different users will have been exposed todifferent A/B tests

These are all properties of your users

UTM tags: source, medium, campaign, terms Landing page Signup time

A/B test buckets Referrer

Viral source

Customer segmentation

Demystifying direct traffic?

Tag all the things!Aim: map all Direct + Referral traffic to a specific source/medium

Do this for Email, Social,Offline(!)..

Tagging guide:- bit.ly/tagging-guide- bit.ly/utm-reference

Landing page: often a big clue to source

Cross-device? Offline channels?

Cross-device?

• Common pattern: Research on mobile/tablet, purchase on tablet/desktop

• Challenge: attribution on mobile

• We need: unique identifying informationE.g. email, mobile/cell #

Cross-device attribution?

https://www.twilio.com/blog/2012/11/increase-app-downloads-with-mobile-app-distribution-powered-by-twilio.html

Filling the attribution blanks..

https://twitter.com/cannonjw/status/432586695490670592

Filling the attribution blanks..

https://twitter.com/cannonjw/status/432586695490670592

Andy Young - @andyy - http://bit.ly/analytics-turing Geographic A/B tests

https://econsultancy.com/blog/64204-12-inspiring-marketing-campaigns-from-google/

Brand vs. non-brand terms for organic + paid search channels

Channel Groupings

Attribution models?

• First touch? Last touch? Multi-touch?

Attribution models?

• First touch? Last touch? Multi-touch?

• First touch: grow our audience reach

• Subsequent touches: grow our conversion rate %

Most campaigns FAIL

Most campaigns fail

..but most every failed campaign will contain partial successes

• Plan in advance: how will we knowat which point in the user journey a campaign failed?

• Do things that don’t scale

Pulling this all together

Why analytics?

What to track?• Discovery / Acquisition • Activation • Engagement • Conversion / Purchase • Retention • Referral

So many platforms

¯\_( )_/¯

What functionality do you need?

What functionality do you need?• Session/Pageview Analytics

Google Analytics, Chartbeat

• User/Event-based analyticsMixpanel/Amplitude, Heap, Kissmetrics, Localytics

• Mobile deep linking and attributionBranch, Adjust, AppsFlyer, Tune, Kochava

• Mobile-specific Flurry, Swrve, Leanplum

• A/B testingOptimizely, WVO, Google Content Experiments, StoreMaven

• Querying & ChartingMode, Periscope, Tableau, RJMetrics, Statsbot

• DashboardsGeckoboard, Klipfolio

• Audience demographics, interests & rankingsQuantcast, Comscore, Alexa, SimilarWeb

• Marketing Automation, CRM, Email & Push NotificationsMarketo, Hubspot, AppBoy, Kahuna

• PlatformsGoogle Firebase, AWS Mobile Analytics

• PlatformsGoogle Firebase, AWS Mobile Analytics😱

How to pick?• What functionality do you need?

• Who will be using it? Devs, data scientists, product folks, marketing people?

• How do you want to use it? Analysis, reporting, dashboards..

• Which platforms? Web, mobile, server?

• Which other tools/data do you need to integrate with?

• What data volumes? Data points, events per second, data points per month.

• Budget?

How to pick?

Things to be wary of:

• Data lock-in, future portability

• Building your own

Tools are not a panacea

Biggest single factor?

Quality of your tracking implementation

- Coverage/depth

- Accuracy/lack of bugs

Andy Young - @andyy - andy@apexa.co.uk

Use a tag manager

Data collection: Segment.com

Andy Young - @andyy - http://bit.ly/analytics-turing 👉 http://sitehound.co

Free code!

Dashboards?

What makes a good dashboard?

Andy Young - @andyy - http://bit.ly/analytics-turing 👉 http://bit.ly/kpi-sheet

Growth model spreadsheet

• Review weekly - zoom out vs. zoom in • Share with whole team • Use to predict and prioritise • What to look at daily vs. weekly vs. monthly

👉 http://bit.ly/kpi-sheet

Metrics are people too

Every metric should be measured inunique people

or % conversion

Joining the dotsPlugging all these tools and platforms together

Initially, manual is OK!

• Forcing function to ensure we: • learn what works • understand the data • need the data

• Paste weekly into a Google Sheet/Excel

Automate over time to reduce effort

Plumbing for automation

• Zapier, Tray.io • Supermetrics, Blockspring for Google Sheets/Excel • Segment.com • Own database/data warehousing - AWS RDS/Redshift • Custom queries - Tableau, Periscope etc

Why analytics?

The numbers never add up

The 5 stages of (Analytics)

The 5 stages of Analytics Grief

•Denial

FB ad clicks vs.

GA visits

•Denial

•Anger

Mixpanel vs. own database

•Denial

•Anger

•Bargaining

Measure Twice: Compare data across different tools

https://jeffpeachey.com/2010/12/02/measure-twice-cut-once-woodcut-for-sale/

•Denial

•Anger

•Bargaining

•Depression

Where did it all go wrong?

Where did it all go wrong?• The data is bad

• Our definitions are wrong

The numbers never add up• Absolute truths

• Signups, Transactional data, UGC, data from our own DB

• Lossy/noisy measurements

• Client-side tracking: GA, Mixpanel/Amplitude etc

• Nuanced definitions

• Uniques vs. totals, funnel conversion rates

Even if the numbers do add up, they are still often misleading

Data discrepancies

Google Analytics vs. Mixpanel

• Definition of unique user - cookie rules

• Ad/tag blockers

Data discrepancies

• Page did not finish loading- e.g. tag manager, or user gave up & hit back button

• Cross-browser JS bugs

•Denial

•Anger

•Bargaining

•Depression

•Acceptance

3-5% discrepancies between platforms?

Roll with it.

Large (>5%) difference?

Debug/analyse to figure out why

Takeaways?

Secrets to successful analytics

• Start with your questions / hypotheses

• Be precise about what to measure, and why

• Plan in advance, simplify

• Automate required work for weekly/monthly calculations

• Document all analysis with simple bullet-points

The numbers tell us What

They don’t tell us Why

Thanks, & good luck!@andyy // andy@apexa.co.uk

Slides: bit.ly/analytics-turing

References & further reading

• My more in-depth analytics presentations: Slideshare, YouTube

• KPI google sheet

• SiteHound website tracking javascript library

• UTM Tagging Guide

• Lean Analytics

• Social Capital blog posts: - Accounting for User Growth

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