Behind every great idea is a great dataDominic Hurst, digital services lead @LJMU dominichurst.com | @dh_analytics

So lets go back in time

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Stakeholder wants

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IT build

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Output?

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“And then what?”

@optimiseordie

#Fail

Lets clear it up…What is data?

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Data isn’t…• (just) quantitative • opinions or assumptions • best practice

Data is…• insightful and actionable • a collaboration (what and why) • your best practice

Slowly, people are appreciating data

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Data appreciation scale

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Minion

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Kim Kardashian

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Arsenal

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Winning!

Where are you?

However, issues prevent us moving forwardimage cc Josephine Saikali

Legacy• mis-treated by “specialists” • marketing (or agency) destroyed reputation to SMT • aggregated, opinionated nonsense • certainly not insightful or actionable

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Legacy - you know…

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Legacy - you know…

Language/ Format• terminology (too much, overlapping) • un-humanistic • incorrect (hit data merged with session data,

internal traffic…) • isolated (quant or qual)

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Not empathic or memorable• numbers • words • forgetful

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So lets change it

#Set goals early • takes time • focus • lean • tell people

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#Set goals early Business objectives - set by senior management Crisp goals - set by the owners of the system KPI’s - thats you (be consistent) Sound targets - back to senior management to set Segment - you again for true insights

You now have a model that is bought into by all kaushik.net/avinash/digital-marketing-and-measurement-model/

interaction-design.org/literature/article/a-simple-introduction-to-lean-ux

#Embed data into process

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Creates and sorts backlog

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Provides understanding

hollidazed.co.uk/2015/07/16/everything-is-hypothesis-driven-design/

Validates the hypothesis

“Because we think [this] is true we think that doing [this] will mean [that this will happen]. We’ll know that this is true/false when we

see this [key performance indicator change].”

Ben Holliday

medium.com/@optimiseordie/hypothesis-kit-2-eff0446e09fc

Validates the hypothesis

“1. Because we saw (qual & quant data) 2. We expect that (change) for (population) will cause (impact(s)) 3. We expect to see (data metric(s) change) within (x business

cycles)”

Craig Sullivan

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Validates experiments

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Aids the build

#Awareness• publicise (dashboards, personas, crib sheets) • in boardrooms, stand-ups • personalise, simple, visual, to the point,

actionable

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On the wall

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In the board room

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On the screen

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Driving personas

#Team game• just like UX, its about the team • show “new” colleagues the potential in your data

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#Culture

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Takeaways

This time, lets look to the future

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Stakeholder wantsUser needs

IT build outputsTeam build outcomes

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1. Data (always)

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2. Visualise

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3. Metrics that matter

Sanity not vanity• Top pages by £ value not top pages by pageviews • Completion rates not just completions • No of tests with uplift not No of tests (per month) • Affect on primary goal not just CTR on the page

econsultancy.com/blog/66434-vanity-versus-sanity-metrics-in-conversion-optimisation/

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4. Keep going

news.toyark.com

5. Data is your friend

Thank you

Dominic Hurst, digital services lead @LJMU dominichurst.com | @dh_analytics