1. Do the algorithms report to the robots?
16 September 2018
Do the algorithms report to the robots?
Michael Ross, Futuretail 2016

2. Changing landscape of data and decisions
NEW ECONOMICS
New variable costs
New revenue drivers
DIGITAL
CONSUMER BEHAVIOUR
Devices
eCommerce
Beacons
Marketing
Empowered
Informed
Unlimited choice
DATA
NEW DECISIONS
Digital enablers
New frequency/logic
Atomised

3. Lots of data Characteristics of data
Resolution: Lots of data at very granular level
Dimensions: Each data point has a lot of attributes
Lots of systems
Each system creates its own digital exhaust
Very granular data
Lots of attributes
And increasingly these data sets can be joined
Clients we work with might send us 100m data points per week

4. Change is hard Retailers making the same decisions with the:
Same organisational silos
Same people
Same capabilities
Same data
Same logic
Same incentives
Same frequency…

5. So what needs to change Physical retail Digital retail
Diagnosis: what’s happened and why
Good enough data and anecdotes
Diagnosis and insight can be delivered algorithmically
Decisions: what to do, what will happen
Experience and simple rules/equations
Predictive and prescriptive analytics required
Delivery: taking the actions
People take action
Specific reporting and digital execution. Convergence = automation

6. ALGORITHM = DATA + LOGIC
How do we automate
ALGORITHM = DATA + LOGIC

7. Algorithms everywhere
Replenishment
Triggered CRM
On-site search ranking
PPC bid management
Markdown/pricing
Ship from store logic
Rules-based
On-site search relevance
Product recommendations
Fraud screening
Pre-targeting
Personalisation
Multivariate testing
Black box

8. Most algorithms are not good
RETARGETING. £6m per annum of retargeting spend sending traffic to products that were sold out
PRODUCT FEED. £2.4m inventory that was not receiving any marketing traffic
SITE SORT ORDER. 1.4m impressions wasted on sold out products
PPC. £7m of paid search spend on Google with no orders
CRM. £4m per annum of sales to 22,000 customers with 100% returns rate
FRAUD. £1.1m of orders per annum from VIP customers getting rejected by new fraud systems
PRICING. £1.5m missed margin – automated markdown taken on products that weren’t being viewed
AB TESTING. £6m lost due to sample bias.

9. Google example: a lot of decisions

10. What it looks like in practice?

11. What goes wrong 23,000 unique keywords £48,753 spend 2,879 orders
Volume of orders 1
2-20
20-100
>100
Total
Cost per order
<£1
£ 21
£ 150
£ 603
£430
£1,204
£1 - £5
£ 173
£ 800
£1,200
£2,173
£6 - £20
£1,344
£ 3,579
£4,923 £
£1,964
£ 6,567
£8,531 £
£3,028
£ 7,394
£10,422 ∞
£21,500
£6,530
£18,490
£1,803
£48,753
23,000 unique keywords
£48,753 spend
2,879 orders
£17 per order

12. How do you manage an algorithm?
New state
Evaluator (actual vs. expected = waste)
Current state
Decision engine
History (data)
Parameters

13. How do we manage….. Wasted spend – e.g., spend with no sales
Spend money inefficiently – e.g., spend above ROI threshold
Missed opportunity – e.g., not spending where efficient
Company-centric [wasted money]
Wasted communications/impressions – e.g., s not opened
Wasted visits – e.g., high bounce, site errors, poor availability
Wasted transactions – e.g., low NPS, missed promise
Customer-centric
[wasted attention]
People-centric
[wasted time]
Wasted effort – e.g., manual changes with no impact
Wasted time – e.g., landing pages not viewed

14. “
At a fulfilment centre recently, one of our Kaizen experts asked me, “I’m in favour of a clean fulfilment centre, but why are you cleaning? Why don’t you eliminate the source of dirt?” ”

15. QUESTIONS