5 Collecting, Analysing And Using Multi Channel Data To Make Better Marketing Decisions ...

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Collecting, analysing and using multi-channel data to make better marketing decisions


We’ll cover

• The multi-channel business• What to collect• How to collect• The analysis process• The decisions we can make


The catalogue business

Housefile Mailings

Requester Mailings

Database

Purchases

Order Data

Catalogue Requests

Space Ads

Card Decks

Lists

OTPInserts


The catalogue and retail business

Catalogue Requests

Housefile Mailings

Requester Mailings

Database

Purchases

Retail

Space Ads

- Walk Bys- PR- Recommended- Thin Air

Purchases

Order Data

Order Data

Lists

OTPInserts


The multi-channel business

Catalogue Requests

Housefile Mailings

Requester Mailings

Database

Purchases

E-mail ProgrammeHome Shopping

Retail

Space Ads


Web

- Natural Search- Paid Search - Online Ads- Affiliates- Thin Air- PR

Orders

Purchases

Order Data

Order Data

Order Data

Lists

OTPInserts


Lists

OTP

Inserts

The integrated multi-channel business

Catalogue Requests

Housefile Mailings

Requester Mailings

Database

Purchases


Retail

Space Ads


Web

- Search Engines- Online Ads- Affiliates- Thin Air- PR

Orders

Purchases

Retail Mailings

Order Data

E-mail ProgrammeRetail



Lists

OTP

Inserts

The integrated multi-channel business

Catalogue Requests

Housefile Mailings

Requester Mailings

Database

Purchases


Retail

Space Ads


Web

- Search Engines- Online Ads- Affiliates- Thin Air- PR

Orders

Purchases

Retail Mailings

Order Data

E-mail ProgrammeRetail



What to collect

• The challenge– Profiling customer behaviour based on transactional data


What to collect

Customer RecordName, Address,

Email, Transaction history, Mailing

preferences


What to collect

Transaction RecordValue, Shipping, Tax,

Date, Item lines, Product (SKU), Quantity, Price,

Channel, Source



preferences


What to collect



Channel, Source



preferences

Marketing RecordSource,

Channel, Date, Promotion


What to collect



Channel, Source



preferences

Marketing RecordSource,

Channel, Date, Promotion


How to collect

• Channel by channel



Housefile Mailings

Requester Mailings

Database

Purchases

Order Data

Catalogue Requests

Space Ads

Card Decks

Lists

OTPInserts


How to collect

• The call centre– Diligent capture

• Mail order– Order form capture



Housefile Mailings

Requester Mailings

Database

Purchases

Order Data

Catalogue Requests

Space Ads

Card Decks

Lists

OTPInserts



Catalogue Requests

Housefile Mailings

Requester Mailings

Database

Purchases

Retail

Space Ads


Purchases

Order Data

Order Data

Lists

OTPInserts


How to collect

• A loyalty card – At point of sale

• Customer details capture– At point of sale

• Or match-back transactions– A dinning table was ordered in-store– To an address for delivery – Has the address received a catalogue?– Is there a correlation between the catalogue mailing and the retail

order and can we therefore attribute a marketing source?



Catalogue Requests

Housefile Mailings

Requester Mailings

Database

Purchases

Retail

Space Ads


Purchases

Order Data

Order Data

Lists

OTPInserts



Catalogue Requests

Housefile Mailings

Requester Mailings

Database

Purchases


Retail

Space Ads


Web


Orders

Purchases

Order Data

Order Data

Order Data

Lists

OTPInserts


How to collect

• Web Analytics tracking– Google Analytics

• On-line traffic source• Multi-channel source• Off-line traffic source


How to collect


How to collect

• www.actionaid.org.uk/sponsor– http://www.actionaid.org.uk/sponsor?

utm_source=tube&utm_medium=outdoor&utm_campaign=ad1

• www.actionaid.org.uk/child– http://www.actionaid.org.uk/sponsor?

utm_source=bus&utm_medium=outdoor&utm_campaign=ad2

• QR (Quick Response Codes)



Catalogue Requests

Housefile Mailings

Requester Mailings

Database

Purchases


Retail

Space Ads


Web


Orders

Purchases

Order Data

Order Data

Order Data

Lists

OTPInserts


What’s possible with Web Analytics

• How visitors found your web site• What visitors are doing on your web site• Not WHY they are doing it!

– Domain of usability/customer experience• Onsite surveys

– Sampling visitors arriving/leaving– 4Q

• Heuristic reviews– Experts reviewing your site against a set of criteria (heuristics)

• Conversion Rate Optimisation– A/B testing– A/B/n testing– Multi-variate testing– Google Website Optimiser– Clicktale– Crazy Egg

• Usability tests– Representative customers completing tasks

» Usertesting.com» Whatuserdo.com


What’s possible with GA?

• How visitors found your website• What visitors are doing on your website

– Not why!

• Outcomes focused

– Goals


Goals

• Goals should be commercial– The commercial goals of your website

• Goals should map to visitor tasks– Visitors visit sites to accomplish tasks

• Tasks normally have a series of steps– Funnel– Measure conversion through the task

• When goals match user tasks– Harmony ensues!


The importance of goals for you

• Commercially justify your work• Focus your work• Prioritise your work


The importance of goals for you

• Goals map to business metrics– Enable you to build a business case for

• Analytics investment• Analysis investment• Action investment

• Goals focus on important paths and entrances– Enable you to home-in on problem areas

• Reverse Goal Path• Conversion to goals by traffic source

• Monetize goals– Enable you to prioritise areas to analyse and optimise

• Give goals a goal value• Analyse $ Index

– (Goal Value + E-commerce value)/unique page views– Page up-to goal contribution– Focus on high $ Index pages for improvement


• You can use Regular Expressions (RegEx) to gain insight into the funnel path:

• User exhibits behavior:– Page 1 = /index.html– Page 2 = /category-footwear.html– Page 3 = /category-clothing.html– Page 4 = /category-headwear.html– Page 5 = /products/kangol-tropic-player-trilby.html– Page 6= /cart/basketview.html– Page 7= /cart/registration.html– Page 8 = /cart/paymentoptions.html– Goal = /cart/salesorderconfirmation.html

• Need to know conversion rate of categories to products to purchase:– Step 1: index\.html– Step 2-4: ^/category.*/– Step 5: ^/products.*/– Step 6: ^/cart/basketview.html– Step 7: ^/cart/registration.html– Step 8 : ^/cart/paymentoptions.html– Goal: ^/cart/salesorderconfirmation.html

Goals and funnels


Goal and funnel behavior


Don’t stop at transactions!

• Goals (with source)– Request a catalogue– E-newsletter registrations– Send to a friend


The analysis process

• Matching back• Recency• Frequency• Monetary• Deeper insight• Continuous insight



• Matching back to source– Channel is always known– Source, is often absent in data capture, so requires

• Correlations between source marketing and transactions• To make good assumptions about source of transaction



• Recency– Take the most recent

discretionary purchase date– Sort by that date and the top

20% (in terms of recency) is given a code of "5".

– The next 20% in terms of recent purchases is coded as "4", etc.

– Everyone in the database now is either a 5, 4, 3, 2, or 1 in terms of recency.

– If you now make a test promotion to a representative sample, you will get a response that looks like this:


Recency

• Recency is the number one most powerful predictor of future behaviour

• Recency is also the most powerful predictor of a customer response to a promotion

• The more recent a customer is– the higher their potential value

• This is a marketing “constant”


Recency decisions (dead certs)

• Use transaction emails to invoke similar behaviour – Promote in high-rate (double) opening email such as:

• Thank you for your order• Your order has been despatched

• Template emails to customers who purchased– 30, 60, 90, 180 and 365 days ago– Seasonal adjustments– Relevant promotions (RFM)

• Announce catalogues dispatch/arrival with emails– 18% uplift in sales



• Frequency– Using the number of transactions with your customers,

code by frequency.– Sort the database from the most to least frequent, coding

the top 20% as "5", and the less frequent quintiles as 4, 3, 2, and 1.


Frequency descisions

• Frequency– Frequent buyers respond better than less frequent buyers,

but the differences are much less pronounced than those for Recency

– The lowest frequency quintile always contains the new customers – who are your best responders.



• Monetary (with Frequency)– Code customers by the total value sales (average and

highest by month, year, or since the beginning of time) giving the big spenders a "5", and the others, 4, 3, 2, and 1.

– Life Cycle of a Customer• Define it by creating a start and end• From first order to last infrequent purchase• Account not just for sales but for profit• “Net present value” of the customer base should be at the

top of the measurement hierarchy– The profit over a period, discounted for the value of money


Monetary decisions

• Monetary– When you do this, you may discover that your top 20%

of your customers gives you 80% of your profits– You may also discover that you can't market profitably

to these top customers, • so you must spend your efforts on service to prevent

defections and market to the next tier down


Combining RFM to form segments

00 - 06 Month

07 - 12 Month

13 - 18 Month

19 - 24 Month

25 - 30 Month

31 - 36 Month

37 - 42 Month

43 - 48 Month

49 - 54 Month

55 - 60 Month

61 - 66 Month

67 - 72 Month

73 Month +

4x+ Multi Total £5.38 £3.20 £2.51 £1.73 £1.33 £1.07 £0.40 £1.86 -£0.74 £0.47 -£0.31 £1.40 -£1.04

3x Multi Total £2.41 £1.24 £0.97 £1.14 £0.15 -£0.04 £0.16 £1.17 £0.07 -£0.84 -£0.74 -£1.01 £1.61

2x Multi Total £1.48 £0.99 £0.27 £0.40 £0.05 £0.90 -£0.28 £0.03 -£0.41 -£0.41 -£0.10 -£0.69 -£0.92

Single Total £0.64 £0.16 £0.15 £0.04 -£0.07 -£0.05 -£0.05 -£0.32 -£0.19 -£0.03 -£0.20 -£0.29 -£0.54

• Which groups contribute most - and least

555

111


Deeper Insight

• Peeking in between the 555s and 111s• Asking questions• RFM segments and original source

– What is the true cost of acquiring a customer?– What are our best (most profitable) recruitment sources?

• RFM segments and sale behaviour– Are our sales attracting the right customer?

• RFM segments and product offerings?– Do first products attract profitable customers?

• RFM segments and promotions?– Do promotions attract profitable customers?

• RFM segments and products and promotions on web pages?– Do first product purchases justify their web page position?


Continuous Insight

• Turn analysis from a picture to movie• Continuous analysis

– Analysis should NOT be an annual event– Continuous transactional data analysis builds most

accurate predictive model

• Analyse to understand channel overlap and identify source– To obtain real cost of customer acquisition

• Monitoring Customer Life Cycle– Net present value of customer– Combine with source

• Identify profitable recruitment methods


To summarise

• Collect, analyse and use transactional data to learn • How best to apportion marketing spend across

– Active customers– Inactive customers– New customer acquisition

• Through which marketing source mix

“If you allocate money away from activities generating low potential value customers, and allocate this money to activities generating higher potential value customers, you will become more profitable over time.”

-Jim Novo


Tools and resources

• http://www.dbmarketing.com– Books and spreadsheets

• http://www.jimnovo.com– Books, spreadsheets and software

• http://www.google.com/analytics– Free Web Analytics

Date post:	21-Jan-2015
Category:	Business
Upload:	ivantage
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5 Collecting, Analysing And Using Multi Channel Data To Make Better Marketing Decisions ...

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