- The document discusses how an online women's fashion brand uses data and analytics to optimize key areas of their business like product listing pages and social media advertising. - It outlines problems around ordering products on listing pages and selecting products for advertising carousels, as well as metrics to consider like revenue, return rates, and stock levels. - Technical implementations are also mentioned, like manually adjusting product orders, publishing ad feeds to URLs, and using Facebook data to personalize listing pages.

1. Putting data to work

2. - Online women’s fashion Brand
- Began trading in Feb 2015
- Over £5m turnover in 2015, 3m visits to website
- On course to do 2.5x in 2016
- 2 people running BI, analytics, online marketing (Facebook + Adwords)
Introduction to Finery

3. Analytics Setup
Internally managed data
integrations

4. Product
Listing Page
PROBLEM
There are 90 styles found on
the example Product Listing
Page. What order should they
be displayed in?

5. Metrics to consider:
- Revenue per Impression
- Return Rate
- Stock Levels
- ‘Coming Soon’ signup value
What order should the
products be displayed in?

6. Product Listing Page Ordering –
Technical Implementation
Website Backend
Manual Adjustments

7. Facebook and Instagram Advertising
PROBLEM
Which 5 products should we
display on our carousels?

8. Facebook and Instagram Advertising
Metrics to consider:
- Revenue per Impression
- Click-Through Rate
- Stock Levels
- Commercial success of the style

9. Facebook and Instagram Advertising
– Technical Implementation
Ad feed published to a URL
(text file)

10. Using Facebook data to inform PLP product order
Pinned products to create a
personalized experience

11. What’s Next?
Related products algorithm