predictive data and analytics for real commercial impact

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Predictive Data and Analytics For Real Commercial Impact Vicky Brock, Tech Innovator of the Year & CEO, Clear Returns @brockvicky www.clearreturns.com Trends, challenges, getting internal traction & a case study on reducing retail returns

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Predictive Data and Analytics For Real Commercial Impact

Vicky Brock, Tech Innovator of the Year & CEO, Clear Returns @brockvicky www.clearreturns.com

Trends, challenges, getting internal traction & a case study on reducing retail returns

Vicky Brock, CEO Clear Returns www.clearreturns.com

The harder I work, the luckier I get !?

[email protected] @brockvicky www.clearreturns.com

Consistently efficient analytics

I measure what matters

I analyse less and act more

I’ve refined my “so what” filters

I trust gut instinct I can’t explain over data that’s too good to be true

I am probably not as smart as you - but:

[email protected] @brockvicky www.clearreturns.com

“give us your datas” Especially

the big ones

The new hot zone!

[email protected] @brockvicky www.clearreturns.com

My structured & unstructured world

[email protected] @brockvicky www.clearreturns.com

Variety? Volume? Veracity? Velocity?

Big data = big pants

[email protected] @brockvicky www.clearreturns.com

Clean is best

Holes = bad

Controlling access is a good thing

It’s what you do with it that counts

messy

vast siloed

mind-blowingly

unknowably irreconcilably

[email protected] @brockvicky www.clearreturns.com

If you’re truly in a big data world

[email protected] @brockvicky www.clearreturns.com

If you’re truly in a big data world

Low on context & business question

led exploration

High on tech & architecture focus, pattern recognition

messy

political siloed

solvable

handle with care solvable

[email protected] @brockvicky www.clearreturns.com

If you’re in a “not technically big” data world

[email protected] @brockvicky www.clearreturns.com

Low on replicable, consistent analytics

process

Huge untapped opportunity for

commercial impact

If you’re in a “not technically big” data world

Building a culture of

So what???

[email protected] @brockvicky www.clearreturns.com

Challenge 1

Do you REALLY know why your organisation does what it does? Have you read – and understood – the annual report & accounts?

Analytics has no value

without action

[email protected] @brockvicky www.clearreturns.com

Challenge 2

Do more with less Break the cycle of analysis paralysis Start somewhere – perfection kills profit and is inefficient

What influences the people who influence you?

Create a data culture Commercial exposure

Understand compensation & KPIs of leadership Questioning, not warfare or procrastination Test , accept failure & mistake, iterate

[email protected] @brockvicky www.clearreturns.com

Challenge 3

Segmentation

Custom responses

Automation

Fraud

[email protected] @brockvicky www.clearreturns.com

Tackle missed opportunities

More £ for equal or less effort

Churn

Top level operational

visibility

Customer segmentation

Stuff that really matters

[email protected] @brockvicky www.clearreturns.com

The pay rise zone

Focus on the big insights

Some real life examples from Clear Returns

Top Tech Start-up in Europe

Big Data Venture Challenge & IBM Smartcamp Winner

Vicky Brock, Tech Innovator of the Year & CEO, Clear Returns @brockvicky www.clearreturns.com

Up to 60% returned

£221 billion preventable retail returns*

& returns are growing faster than sales

*Returns cost retailers £435billion globally, with £221billion deemed preventable. IHL Group, Retail Analysts, June 2015

Can’t be resold as new

Faulty?

It’s not a sale until the shopper decides to keep it

Clear Returns SaaS intelligence platform helps retailers retain £1million extra revenue per £10million refunded

Because once returns are factored in, not all customers are equally loyal or profitable & not all product covers its costs

Retain more

revenue

Cut costs and

wastage

Improve customer

experience & lifetime

spend

Improved buying

decisions & stock

coverage

Optimise profits

First time & high value customers are disproportionately affected by product/expectation gap issue

@clearreturns @brockvicky

[email protected] @brockvicky www.clearreturns.com

Problem products are extra costly

10% of products cause up to 50% of returns impacts

Not all products return equally

Early warning...

Predicting the returns the retailer hasn’t bought yet

So what?? So What??

Problem products are extra costly

Early warning on problem products & returns sensitive customers is key

Prediction means problems fixed fast

Marketing can turn calm kitties into crazy returns monsters

1% customers cause up to 10% of returns costs

Not all customers return equally

@clearreturns | www.clearreturns.com | 0141 554 4175 | [email protected]

[email protected]

0141 554 4175 www.clearreturns.com

Vicky Brock, CEO 0141 554 4175 www.clearreturns.com

Thank you