uncovering the potential of online marketing blind spots
TRANSCRIPT
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Data: How to eat an elephant
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Hi! We are Robbe & Lieselotte
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We work @ WijsA digital Agency in Ghent
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Our behaviour has changed
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Big data
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Oh no, not again…
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Product development
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Customer service
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“Whether you like it or not, you’re gonna have to get to know your customer in a way you have never before”
KNOW YOUR CUSTOMER
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You are not alone
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‣ Existing IT-infrastructure in companies
‣ 95% does not yet have a vision on data-infrastructure
‣ GA is just a little part of the whole data-infrastructure
Boundaries within companies
Adoption barriers, 2 grote:1. Infrastructuur => 95% nog geen visie rond infrastructuren voor data. Wij werken op GA, maar is slechts deeltje van hele data-infrastructuur2. Analytics & infrastructure => vaak 2 aparte departementen. Data & technology - marketing & IT + biz departement => deze 3 partijen moeten consensus hebben om te werken rond big data => Intelligence team (ambassadors)
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MarketingIT
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Source: http://knowledgent.com/whitepaper/2015-big-data-survey-current-implementation-challenges/
Boundaries within companies
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We are becoming…
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Tip 1
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IT Business
Marketing
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Use multidisciplinary teams
ITMarketing
Business
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Tip 2
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Unravel your data…in phases
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Web
Analytics
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Google Analytics
‣ Clickstream data analysis ‣ Customer lifetime value
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But before you start… Get your basics right
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‣ Safety profiles (raw, sandbox)
‣ Exclude (all) spambots
‣ Update tracking code to UA
‣ Enhanced e-commerce tracking
‣ Campaign tracking
‣ Exclude internal traffic
‣ …
Get your basics right
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Web
Analytics
Other internal data
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Tip 3
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4 STEPS
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Analyse your thoughts, not the data!
1
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Do our customers actually buy more than once?
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2 Make Hypotheses of your thoughts
AND
Amplify
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80% of the solution starts with the hypothesis
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Do our customers actually buy more than once?
Hypothesis 1 = Do our customers buy more than once
Hypothesis 2 = Do men (our main target audience) buy more than once?
Hypothesis 3 = Men who bought more than once how many times do they buy online and offline
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3
Decompose the hypothesis
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Men who bought more than once how many times do they buy online and offline
Gender # purchases Online purchases
Offline purchases
Hypothesis 3 = Men who bought more than one time how many times do they buy online and offline
# Online purchases + Offline purchases
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4
Where can we get these variables (with Correct values)
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• Find that ID to connect to.
• Upload (manual or automatic) the basic variables you need
Start analysing!
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Web
Analytics
Other internal data
External data
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Source: http://www.simoahava.com/analytics/send-weather-data-to-google-analytics-in-gtm-v2/
Weather
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Retail
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We’ve been trying out with one of our clients
“1/5th less online purchases when it’s raining”
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‣ Geolocation API: Approximation of location where person is browsing from
‣ Openweather API: Use geolocation to define weather on that moment in visitors region
‣ GTM: Store all information in Data layer to be available for our tags
=> Send data layer to newly made custom dimensions
How to start with this?
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1. Multidisciplinary teams
2. Peels / Phases
1. Get your basics right
2. Connect your internal data
3. Get external data
3. Don’t try everything at once. Use hypothesis methode
Key takeaways
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Questions?
Robbe Lammerant Online marketeer
Lieselotte Van Tieghem Operational Director