John Morton Effective use of (Big) data driving informed marketing

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Executive Leaders Network – June 2016Twitter: @JohnFMorton01/05/2023 1

EFFECTIVE USE OF (BIG) DATA DRIVING INFORMED MARKETING Although big data, associated technologies, data science and methods have been used in some commercial areas since the 1980’s; the advances in technology and commoditisation of technology has provided smaller companies with the capability to take advantage of the technology, thus driving better profit margins, identify new markets, and disrupting existing “players”, insurance, retail banking, taxis and retail are in various states of flux.

In digital businesses the dynamics mean that marketeers are faced with continuous pricing, continuous segmentation, and understanding buyers behaviour(KYC). The revenue per customer model is no longer valid; “value per customer” is the focus.

Marketeers are now expected to interweve all of these and discover the “ideal customers” to acquire and retain.

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EFFECTIVE USE OF (BIG) DATA DRIVING INFORMED

MARKETING

John MortonExecutive Leaders NetworkJune 2016Twitter: @JohnFMortonExecutive Leaders Network – June 2016





Marketing Sales Delivery/Retention/Repeat Sales When does marketing stop?

Prospects




CLASSIC METRICSOperational Metrics

· Customer Revenue: · Customer Satisfaction: · Customer Profitability: · Customer Lifetime Value: · Brand Awareness: · Customer Loyalty: · Conversion Rate: · Completion Rate: · Churn Rate: · Retention Rate:

CEO Metrics 1) Customer Acquisition Cost (CAC)

2) Marketing % of Customer Acquisition Cost (M%-CAC)

3) Ratio of Customer Lifetime Value to CAC (LTV:CAC)

4) Time to Payback CAC 5) Marketing Originated Customer %

6) Marketing Influenced Customer %

revenue per custo

mer model




DataSources

MarketingAttitudinalInteractionWebMobileCall-centerOperationalIOTPartner dataOpen Data

Customer Contact Channels

WebsiteEmailPhoneMailBranchATMB2BAgentMobileIOT…

DATA AND CHANNELS What are the optimum channels to engage with the customer?What type of forum/device/tool is relevant for this customer ?

What content and offers are relevant/not relevant ?

What contact mechanisms, themes and treatments increase customer value? What data do I need to increase customer value/retention/advocacy?




SO WHAT ABOUT CUSTOMER VALUE ?

Activity costing

Product(s)/Service(s)

costImplementati

on costingLocal,

locationor transfer

costs

Cost of Customer

(Acq. /Dev. /Ret.)

Cost of infrastructure

$

¥

£

€} =?




CHALLENGER BRANDS

P

Chal

leng

er S

egm

ent

ProfitChallenger Segment- Pricing- Customers- Locations- Methods- Targets- Revenue- Profit- Challenger Value

- Flexible- Focussed- Better relevant data- Responsive

Chal

leng

er S

egm

ent

Chal

leng

er S

egm

ent

Chal

leng

er S

egm

ent




Behavioral data- Orders- Transactions- Payment history- Usage history

Descriptive data- Attributes- Characteristics- Self-declared info- (Geo)demographics

Attitudinal data- Opinions- Preferences- Needs- Desires

Interaction data- Offers- Results- Context- Click streams- Notes

Web dataUp to 20%better predictions

Text dataUp to 40%better predictions

AttitudesUp to 30%better predictions

DataSources

MarketingAttitudinalInteractionWebMobileCall-centerOperationalIOTPartner dataOpen Data

Customer Contact Channels

WebsiteEmailPhoneMailBranchATMB2BAgentMobileIOT…

BETTER DATA, BETTER INSIGHT







VALUE ZONE

Value

Time




CHALLENGES Trust of Data – Have the right quality metrics TrustedSemi-trustedUntrustedPerishablePersistent

Information Gain What does the ……….. say? Actionable data?



Executive Leaders Network – June 2016Twitter: @JohnFMorton 12

DATA BUSINESS VALUE FRAMEWORK

0Business Value

+-

+

0Data

Effectiveness

-

Improved Data effectiveness

with no business value

penalty

Improved business value with little or no

data effectiveness

penalty

Data Driven Value

Requires incremental

budget

Necessary, but low value

Creates resistance from line of

business and users

Failure

Failure

Failure

Win – Win




CUSTOMER VALUE METRICSOperational Metrics

· Customer Revenue: · Customer non-Satisfaction: · Customer Profitability: · Customer Lifetime Value: · Brand Awareness: · Transfer to effective servicing - Customer referral/advocacy cost

· Conversion Rate: · Completion Rate: · Returned Customer rate (Nudged):

· Retention Potential:

CEO Metrics1. Customer Acquisition Cost (CAC) 2. Value per customer(post initial)3. Marketing % of Customer

Acquisition Cost (M%-CAC) (initial and retained)

4. Ratio of Customer Lifetime Value to CAC (LTV:CAC)

5. Time to Payback CAC 6. Marketing Originated Customer %7. Customer referral/advocacy %8. Marketing Retained Customer %9. Initial Buyer Churn Rate 10.Value Zone Churn Rate




SOME EXAMPLES: Lenovo listens to its customers on social media so that it can stay on top of trends, such as colour preferences for laptops.

Société de Transport de Montréal (STM) offers promotional offers based on the location of its customers so they can try a new restaurant or shop when they got off at their stop.

Thule provider of premium vehicle accessories including roof racks, sports carriers, and other recreational products, increased sales by 20% simplifying demand through to order process. 37% increase in customer service capability, released to support sales enquiries and follow-up.

Brompton Creating a community to drive retention, cross sell and brand.

Telecomms Using advocates to drive trial offers and assess market positioning.




SOME PARTING THOUGHTS?What new metrics make sense in your business?How do I convince my board, drive adoption?What data is costing me more than the value it delivers? How can I streamline “data capture” to “data action”? What technology will get the best out of my data?When my business needs, or competitive landscape change, will the technology adapt?




QUESTIONS?

Eur. Ing. John Morton BSc, CEng. FBCS, CITP, [email protected] +44 7771 740203Twitter @JohnFMortonThanks to Pixabay for Images

Applying People and Technology to Business





ANALYTICS SUPPORTING PRICING

Business as Usual Prices are set regionally or by products

Promotional pricing offered on new term deposits

When promotional pricing lapses Some customers leave Other roll-over their deposits

Promotional and go-to prices vary significantly Across regions Over-time Relative to competition

Analytic pricing Statistically predict customers sensitivity by product by price to pricing strategy

Target the right price for the customer

Consciously control funds for customer retention




CHALLENGES REMAIN THE SAME Market versus product versus price Harvesting versus Demand Generation Retention versus “time to leave” Identifying coimmunities and building communities




BUSINESS ANALYTICS ECO-SYSTEM

Data assets

Analyticsstrategy

Value propositions

ICT strategy

HR strategy

Business strategy

Vidgen, R., (2014). Creating business value from Big Data and business analytics: organisational, managerial and human resource implications. Hull University Business School Research Memorandum, no. 94, ISBN 978-1-906422-31-8.




MARKET BASKET ANALYSISClassical Advanced next product to

Buy Basket = Collection of Customer Specific data that may include:

Socio-demographics Product portfolio Transactional Behaviour Contact history Debt and payments history




RECOMMENDATION ENGINES

Revenue 5-15% overall revenue increaseEngagement 12 – 18% of visitors engaged with product

recommendationsAverage Order Value

30-70% increase – visitors who engage with recommendations

Conversion Rate 2-4x increase – visitors who Saving Staff Time

Elimination of manual Content Management effort

Items per Order 20-40% increase- visitors who engage with recommendations
