Data: How to eat an elephant

Hi! We are Robbe & Lieselotte

We work @ WijsA digital Agency in Ghent

Our behaviour has changed

Big data

Oh no, not again…

Product development

Customer service

“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

You are not alone

‣ 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)

MarketingIT

Source: http://knowledgent.com/whitepaper/2015-big-data-survey-current-implementation-challenges/

Boundaries within companies

We are becoming…

Tip 1

IT Business

Marketing

Use multidisciplinary teams

ITMarketing

Business

Tip 2

Unravel your data…in phases

Web

Analytics

Google Analytics

‣ Clickstream data analysis ‣ Customer lifetime value

But before you start… Get your basics right

‣ 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

Web

Analytics

Other internal data

Tip 3

4 STEPS

Analyse your thoughts, not the data!

1

Do our customers actually buy more than once?

2 Make Hypotheses of your thoughts

AND

Amplify

80% of the solution starts with the hypothesis

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

3

Decompose the hypothesis

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

4

Where can we get these variables (with Correct values)

• Find that ID to connect to.

• Upload (manual or automatic) the basic variables you need

Start analysing!

Web

Analytics

Other internal data

External data

Source: http://www.simoahava.com/analytics/send-weather-data-to-google-analytics-in-gtm-v2/

Weather

Retail

We’ve been trying out with one of our clients

“1/5th less online purchases when it’s raining”

‣ 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?

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

Questions?

Robbe Lammerant Online marketeer

Lieselotte Van Tieghem Operational Director