111236462 Equations of Retail

5/27/2018 111236462 Equations of Retail

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The newequationsof retail


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The new equations of retail

A common complaint of the retail CEO confronted with thetsunami of online data is now what?

The new equations of retailMichael Ross Chief Scientist and Co-founder, eCommera

Retail is about thousands of small decisions

so the question should be: what new or differentdecisions should we make given this data?Three things make this difficult:

New activities Google, site sort orders,CRM, delivery to customers are all generallynew disciplines for retailers, and require newskills

New data each of these activities generates

its own torrent of data which needs to becollected and understood

New costs the cost per click of Google,the variable costs of picking/packing/shipping,cost of communicating with customers.New costs change the economics of retail.

New activities mean new decisions. And newcosts mean different decisions. These decisions

require rules. And the new data allows rules tobe codified what we (somewhat) grandly callthe new equations of retail.

This article gives five examples (out of the

hundreds of possible examples) of the sorts ofscenarios where new and different decisions needto be made and where its easy to get it wrong.

How much is it worth investing in the serviceexperience?

What profit per order maximises your overallprofit?

How much should you spend on a keywordon Google that hasnt generated any sales?

What combination of markdown and productviews maximises profit?

When should you target a customer who hasstopped purchasing?

This article sheds some light on these questions.


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In physical retail, operations is back of house,focused on getting product to store. In the onlineworld, operations is the last touch point with thecustomer, and is fundamental to success, but it isoften handled by exactly the same people, and inexactly the same way.

For most retailers, this is not the exciting part ofeCommerce. Theres no whizzy new technologyto play with and no social opportunity yetoperational excellence is critical for success.Imagine a typical situation: you get a 600 orderat 2.30pm from a first time customer who hasselected a different billing and shipping address,with next day delivery.

Do you:(i)Do everything possible to ship it same day(ii)Do a standard fraud check but insist that the

first order is delivered to the billing address(iii)Do a rigorous fraud check and probably miss

the delivery promise.

The likes of Amazon and Net-a-Porter can simplydecide to make service a focus and have amessianic belief that its the right thing to do. Forthe majority of retailers, their CEOs and boardsrequire convincing that this is the right place toinvest.

A key operational question therefore is howcan you make the trade-off of between cost vs.service?

The Maths

Intuitively it is obvious that better service drivescustomer retention, but how do you quantifythe value of service? Whats the equation that

tells you when to stop investing? The key is tounderstand the relationship between service andcustomer retention, and then to quantify the valueof retaining customers. A typical analysis is below:

OPERATIONS:Whats the value of service?

Figure 1: Delivery on promise

-3%

TODAY

TODAY

MorePro

fit

LessProfit

Better serviceWorse service

-2% -1% +1% +2% +3% +4%

Incrementalcustomerlifetime value

Incrementalprofit

INPUTS

Impact of delivery on promise on

customer satisfaction

Impact of customer satisfaction on repeat purchase rate

Impact of repeat purchase rate on customer

lifetime value (LTV)

Cost of improvement to delivery of promise

Optimisationopportunity


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Once the relationship between cost and servicehas been established new processes need tobe put in place. Of particular importanceare automated fraud processing, orderprioritisation/routing, order cut-off times,carrier pick up time, shift patterns, weekend

working (to avoid a Monday backlog), etc.

For example, Figleaves had a focus that all in-stock orders placed by 4pm should be shippedsame day and the warehouse managers dailyreport showed orders placed by 4pm notshipped.

It is vital to develop processes that make failingon promise unacceptable. In the early days of

Net-a-Porter, orders from VIP customers wereprinted on pink paper so they stood out in thewarehouse, with a mandate that all VIP ordershad to ship same day. Operational magic!


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In physical retail, marketing is either non-existent(high street rent obviates the need for marketing)or is a fixed annual spend. As one retailer told merecently, our marketing strategy is deciding howmuch we will spend on TV at the beginning of theyear. In addition, the variable costs of sale in store

are negligible typically a carrier bag and creditcard charge. In physical retail, all transactions(outside of sale and clearance) make money.

The profit model online is different. Its very easyto lose money on an online order. Firstly, mostmarketing is a variable cost whether per order, perclick, or per impression. Add to this variabilitya delivery charge (which could be greater, equalor less than the directly associated costs) and

promotion costs.

Tough-minded retailers often announce thatthey want to make money on every order theyship. This statement sounds sensible but is

(i) not what it seems and (ii) is definitely not theway to optimise profits.

Firstly, aspiring to make money on every orderis primarily a statement about the granularityof marketing allocation. Why? Look at the

marketing cost of an example order, the visitorclicked on Google and that visit cost 27 pence, sothe individual order looks very profitable.

However, you then note that this profitable orderis accompanied by 300 visits that didnt convert.So the order is profitable but the marketingactivity directly associated with the order isnt.

Secondly, ensuring that all orders are profitable is

clearly a different statement to ensuring that theoverall profit is maximised. Imagine a retailer witha 10 delivery charge this may guarantee thatevery order shipped makes money; unfortunately,a high delivery charge has a negative impact on

MARKETING:Whats the right profit per order?

Figure 2 Understanding profit per order

Gross tradingprofit

Gross profitper order

Marketing costper visit

Conversionrate

Promotioncost per order

Marketing costper order

Delivery revenue/cost per order

Average order

value

Gross margin

x

Number oforders

Trading profitper order

x

x

Online visitors


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conversion rate, and will depress the volume oforders. So, a core marketing question to ask iswhat profit per order maximises overall profit?

The Maths

Maximising overall profit requires the rightbalance of marketing spend, delivery charge andpromotion cost. To give a simple example, aretailer makes more money from 5,000 orders at5 profit per order, than 2,000 orders at 10 profitper order.

The critical equation to understand is whatdistribution of order profitability maximises totalprofit (and the optimal profit will typically come

with some loss making orders). For example,ASOS offer free delivery and free returns in theUK. It is unlikely they made any money on the 3

Figure 3:Profit per order

AVERAGE18.20

CURRENT DISTRIBUTIONOF ORDER PROFITABILITY

OVERALL PROFIT

40

Profit per order

Number of orders

TODAYMore

promotionalLesspromotional

5 10 15 20 25


Averageprofit

per order

ILLUSTRATIVE

TODAY

Moreprofit

Lessprofit

order I placed for an earring multipack, but theoverall business is extremely profitable.

Online retailers need to recognise that monitoringand managing the distribution of orderprofitability is a new discipline. They should

monitor competitors delivery charges, freedelivery thresholds and the availability of widelyavailable discount codes. Offering free/reduceddelivery by stealth (i.e., without marketing) isa great way to understand the latent elasticitywithout creating a call to action.

There are creative ways to manage orderprofitability: for example, Zappos treatspromotions, marketing and delivery as a single

pot so that free delivery becomes a promotionalactivity funded by marketing.


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www.ecommera.com

MERCHANDISING Lower price or more traffic?

In physical retail products either sell or dont sell.For those that dont sell, the action is blunt reduce their price. Whether buyer or merchandiser,the ownership of the performance is clear. Thiscombination of the physical cost of markingdown and the well understood price elasticity

means that most retailers typically have a maturediscount schedule. For example, most fashionretailers have a 30-50-70 percentage pointdiscount approach.

Online the product economics are different.Product views have a cost and you can forexample drive traffic from Google to specificproducts. For merchandising therefore, a keyquestion is Do you get a better return from 100

more visits or a 10 percent discount?

The Maths

Online retailers need to understand the optimalprice/views mix that maximises product

profitability (do you give money to Google orcustomers?). The maths requires understandingthe relative elasticity of price versus traffic. Atypical analysis is below.

Once this relationship is understood the next

challenge is one of cultural change. Merchandisingteams must learn to make discounting decisionsusing analytics data. Buyers incentivised purelyon achieved product margin have little interest inworrying about end-to-end product economics.Similarly, marketing teams incentivised on a costper order dont worry about gross margin.

I asked the CEO of a US department store how hegot his buyers and merchandisers to engage in this

sort of analytically driven markdown approach.He replied: If buyers/merchandisers come tome to approve a markdown and dont have anyanalytics data, its a short meeting.

Figure 4: Price/views to optimise product profit ILLUSTRATIVE

PRODUCT VIEWS

Totalproductcontribution,

000

(Margindirectmarketing)

Optimal strategy to reduceprice and views

20% off Full retail price

200 300 400 600 700 800100

10

20

30

40

50

60


TODAY

7


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Most retailers are spending between 10-30 percent of their paid search budget on keywords thathave never generated a sale. Often retailers simplylook at their blended overall Google performanceand accept (either implicitly or explicitly) thatthe efficient spend can subsidise the inefficient

spend. Its a dangerous game equivalent toaccepting that profitable stores can subsidiseunprofitable stores and is simply a waste ofmoney. Optimising Google requires optimising ona keyword by keyword basis.

For example, imagine you start bidding on anew keyword Canon Ixus 230hs whichhasnt generated any sales (on any attribution

window) after 5 visits, 10 visits, 100 visits,1000 visits when do you stop? Stop too soonand you will miss sales, stop too late and onlyGoogle wins.

A critical marketing question then is How do

you determine the optimal stopping point for anew keyword?

The Maths

The maths of paid search is horribly complex.Google has created a deceptively simple model you pay per click. How hard can it be? In realityit is an enormous mathematical puzzle.

MARKETING:How much to spend on

a keyword with no sales?

10 15 20 25 30 35 405

0

10

20

30

40

50

Figure 5:Optimal stopping point for example keyword

Expectedprofit

Optimal stopping pointLifetime value

Optimal stopping point1st order profit

INPUTS:

Example for CanonIxus 230hs

Cost per click W pence

Product grossmargin X

Expected customerlifetime value Y

Target customeracquistion cost for thiskeyword Z

Informed priordistributionassumption

-20

-10 Number of visitswith no sale


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The maths requires understanding after howmany clicks to stop spending. The analysisabove shows the relationship between theexpected profit versus the number of visitswithout a sale.

There are a wide range of new activitiesand processes that are required to managethousands of long tail keywords. If a keywordisnt working, its easy to simply switch it off,however that may not be the best action to take.The new processes include:

Checking price/availability (dont blameGoogle if youre out of stock or overpriced)

Checking match type its easy for broad

match keywords to pollute performance Checking landing pages/copy (looking at

bounce, engagement, quality score its easyfor landing pages to become out of date)

More targeted bidding by geography or timeof day for example, we found at Figleavesthat bidding on the keyword lingerie wasless economic late at night.

Google are the virtual landlords of the high

street. And as on the high street, no one likes toover pay on rent!


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In physical retail customers are typicallyanonymous.

By contrast the online world affords untoldinformation about your customers. It is clearly aretailers prerogative to decide (i) whether to look

at this data, and (ii) what action to take. Doingnothing is a strategy and there are many verysuccessful retailers today who succeed withouttapping into any deep customer insight.For those that do look, the question is what toactually do. Take a customer (John) who hasspent 1200 over the last 3 years, making 12purchases. Johns last purchase was 6 months

ago. Do you: (i) do nothing, (ii) send an emailpromotion, (iii) retarget John with a banneradvert, or (iv) call John?

Common wisdom is that a customer who hasntpurchased for 6 months is lapsing and after

12 months is lapsed. These are clearly broadgeneralisations. Every category has its ownpurchasing rhythm.

So a key question on customer next best action toask yourself is: When is the optimal time to targeta customer who hasnt purchased?

CUSTOMER NEXT BEST ACTION:When is a customer lapsed?

Figure 6: Optimal intervention point ILLUSTRATIVE

Incrementa

llifetimevalue

Weekssince purchase

10% promotion20% promotion

Optimal intervention point

1 2 3 4 5 6 8 9 10


TODAY


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The Maths

It is critical to analyse and understand the impacton customer lifetime value of different promotionsat different times post purchase.

Offering a discount on the next order immediatelymay be too soon, after 12 months may be toolate. The optimum time will be different for eachbusiness.

For example the Economist designed a renewalat birth campaign after recognising that the besttime to renew a subscription was just after it hadbeen taken out.

Moving from broadcast to targetedcommunications requires building a customer-centric marketing capability with a culture ofdisciplined testing. Many organisations claimto be customer-centric with a test and learnculture. Few act like this in practice truecustomer centricity is difficult and most retailerslike the concept of test and learn, but dont like tomake mistakes.

***

As Richard Feynmann who won the NobelPrize for Physics often remarked, If anyonetells me they understand quantum mechanics,they dont. I feel the same is true of most

aspects of eCommerce.

eCommerce is still in its infancy and many ofthe new equations are simply unsolved. Thebest ecommerce practitioners know what theydont know.


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+44 (0)20 7291 5800www.ecommera.com

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111236462 Equations of Retail

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