Door het razende tempo waarin technologische ontwikkelingen elkaar opvolgen, gaan consumenten verwachtingen ten aanzien van bedrijven door het dak. Elke interactie moet een hyper-gepersonaliseerde ervaring zijn en services moeten accuraat en on-demand geleverd worden. Dit alles het liefst in een vlotte, consistente klantreis. Dit heeft grote impact op de werkwijze en processen van retailers en e-commerce partijen. We zien vele projecten starten om aan deze torenhoge verwachtingen te voldoen, maar vaak blijkt de stap naar een data science oplossing in productie een lastig vraagstuk. Erwin zal tijdens zijn presentatie data science zijn ervaringen delen over grote innovatie trajecten bij vooraanstaande merken en dieper ingaan op de belangrijkste valkuilen uit de praktijk. Je zal leren hoe je hier als manager en organisatie mee om kan gaan en zelf aan de slag kan om ook jouw consument met diep gepersonaliseerde producten en services van dienst kun zijn.

1.  Machine learning in Retail: de basis voor een sterke omni-channel strategie
2020-01-30 – Webwinkel Vakdagen

2. Erwin van Oosten
Captain Commercial Organization at Building Blocks
We are challengers
Experts in consumer data science
We blend technology and consultancy

3. Building Blocks empowers companies to understand and act in consumers’ favor
Our mission
Our mission is to empower every consumer-
focused company understand and act in
consumers’ favor

4. Many technological innovations are continuously changing consumer contexts
Where do you stand?
Consumers are changing rapidly

5. 5 |
Consumer expectations and desires are going increasing exponentially
Brands should focus on building long term relationships with their consumers
The consumer expects:
Personalized content and products
Easy and seamless experiences
Instant on-demand services
Trustworthy relationships
Consumer brands should meet these expectations to
build long-term relationships with their consumers
rather than focus on short-term successes.

6. Consumer analytics are critical for success
Making good use of data (science) is difficult
We help you to achieve your goals and build trustworthy consumer experiences
Let’s turn your plans and ambitions into reality together!
Your plan Reality

7. Data science belongs to the IT and/or analytics department
Pitfall 1
Pitfall 1
Data science belongs to the IT
and/or analytics department of my
organization

8. 8 |
Data science becomes a core capability of everyone in the organization
Artificial assistance for individual holiday recommendations
Corné Hoogendoorn – Marketing Director
Building Blocks personalized almost every
aspect of our customer journey. A unique
collaboration in which every consultant is
dedicated to achieve the best results for
Corendon.
Results:
54% conversion ratio increase
98% less unsubscribes for e-mail marketing
Dynamic landing page
Customer service with a personal touch
Dynamic landing page
and real-time recommendations
Up- and cross sell via customer
service
Perfectly timed and
personalized e-mails

9. Too much focus on exotic innovations
Pitfall 2
Pitfall 2
Too much focus on exotic
innovations, and too less on
business impact

10. 10 |
Use data science to support and optimize the business you run today
Dynamic pricing and personalized recommendations
Philipp Bössem – Marketing Manager
Building Blocks has a great hands-on mentality
and adds true value to our business. Nothing is
better than exceeding expectations and being
positively surprised.
Results:
23% revenue increase
99% conversion increase on recommended products
28% revenue increase from comparison websites
38% more visits from comparison websites

11. Data science is only there for full automization processes and decision making
Pitfall 3
Pitfall 3
Data science is only to fully
automize processes and decision
making

12. 12 |
Humans and AI should work together: use it to support decision making
Smart assortment and intelligent replenishment
Eliska Punselie – Key Accountmanager
Building Blocks created a easy to use predictive
dashboard for our complex assortment
decisions. Improving the way we work, but most
importantly helped us to increase our sales.
Results:
7.5% turnover increase
19.1% lost sales decrease customers
21% decrease in redundant stock for slow moving products

13. Data science is a one-off implementation
Pitfall 4
Pitfall 4
Data science is a one-off
implementation

14. 14 |
Data science is a process of continuous optimization
Improve the speed and accuracy of your customer service center by creating a collective memory
Results:
8% more time-efficient interactions
Daan van der Mijden – Sr. Director Customer Care
I am proud to have been able to work with Building
Blocks and Teleperformance to develop this Collective
Memory solution, and am enthusiastic about our future
collaboration

15. 15 |
Learnings and key take-aways
Start cases with high volume data you are used to work with
Data science is a process of continuous optimization
Close the gap between business and technology
Don’t rely on models for 100%, context and business knowledge are crucial
factors for success
Start small, experiment and proof value before automatic integration in
business infrastructure
Have a clear goal and KPIs in mind: know what and how to measure success

16.  Thanks for your attention!
Consumer predictions for retail and insurance