Dr. Ehud Reiter, Computing Science, University of Aberdeen1 E-Commerce – customer focus l...

Dr. Ehud Reiter, Computing Science, University of Aberdeen 1

E-Commerce – customer focus

Attracting and keeping customers» Issue: security, trust

Legal issues Personalisation Adverts


Customers are different!

Consumer types» Individual consumers» Organizational buyers

Goal of shopping» Pragmatic: buy something useful, cheaply» Hedonic: have fun

Personality» Impulsive buyers—purchase quickly» Patient buyers—make some comparisons first» Analytical buyers—do substantial research before buying


Consumer Behaviour

Prentice Hall, 2002


Consumer Satisfaction

Prentice Hall, 2002


Security/Trust

Security/trust» Will the company actually deliver the

correct product in reasonable shape, in a reasonable time, at correct price

» Will the customer pay up (is the credit card stolen, will it be repudiated)

Technical aspects Human aspects: Focus here on trust


Trust in physical shops

Experience: shoppers trust shops they’ve used before

Appearance: shoppers trust store that look reputable

Complaints: easy to complain, shop can’t hide

Transactions are simple


On-line trust

What makes you trust an e-commerce shop?


On-line Trust

Experience: I trust Amazon because I’ve used them before» Reputation: because my friends use them» Very important with e-shops

Appearance: do I trust Amazon because they have a nice website???» Less important than with physical shops» Marketing helps


On-line trust

Complaints: Harder to complain since don’t know where shop is

Transactions are complex because of delivery» Where many e-shops mess up

Third-party: do I trust Amazon more if another web site says good things about Amazon (???)


Does Amazon Trust Me?

Amazon trusts me because» Experience: I’ve always paid Amazon

before» Reputation: I’ve used other companies and

always paid up» Marketing: Amazon threatens nasty things

to customers who don’t pay up


Trust

We know how trust is established in physical shops.

We are developing mechanisms for establishing trust in e-shops» Partially technology, but psychology and

sociology probably matter more» Lack of trust mechanisms is barrier to new

e-shops


Legal Issues: Tax

In USA, one driving force behind early e-store success was less tax» Because of a tax loophole, sales tax (VAT)

was not charged on e-commerce sales Automatically gave price advantage to

e-commerce sites!


Legal Issues: Intl E-Commerce

In theory, e-commerce means sites can sell globally

In practice, difficult because of different tax rules, regulations, customs, etc» More common to set up subsidiaries in

different countries, as Amazon has done Lack of global legal/regulatory

framework hinders ecommerce


Personalisation

E-Commerce sites can treat customers differently» Offer recommendations, special deals» Personalise web site» Adjust prices

In theory, “personalised shop” one of the great benefits of e-commerce

One-to-One MarketingBuild a long term association

Meeting customers cognitive needs Customer may have novice, intermediate or expert skill

E-loyalty—customer’s loyalty to an e-tailer costs Amazon $15 to acquire a new customer costs Amazon $2 to $4 to keep an existing customer

Trust in EC Deterrence-based —threat of punishment Knowledge-based —reputation Identification-based —empathy and common values Referrals – Viral Marketing

Personalisation…

Personalisation - Marketing Model“Treat different customers differently”

Prentice Hall, 2002

Personalisation“Process of matching content, services, or

products to individuals’ preferences”

Build profiles – N.B. Privacy Issues Solicit information from users Use cookies to observe online behavior Use data or Web mining


Recommendation

Build profiles» What has X bought?» What has X looked at?» Demographics: age, gender, etc

Recommendation» Rules: If X buys Harry Potter 6, recommend HP 7» Data Mining: Other people who bought Harry

Potter also bought Lord of the Rings» Collaborative: X’s overall buying profile is similar

to Y, so recommend whatever Y bought

Data Mining

Automated prediction of trends and behaviors Example: from data on past promotional mailings, find out

targets most likely to respond in future

Automated discovery of previously unknown patterns Example: find seemingly unrelated products often purchased

together Example: Find anomalous data representing data entry errors

Mining tools: Neural computing Intelligent agents Association analysis - statistical rules

Web Mining - Mining meaningful patterns from Web resources Web content mining – searching Web documents Web usage mining – searching Web access logs

searching for valuable information in extremely large databases


Recommendations

If done well, perceived very positively» Real benefit, not just marketing spam» Credit-card companies have done this well

– Have the most purchasing data?

Data privacy issues» Can Visa sell data about you to Amazon?» Spyware to track all of your web browsing?


Personalise Web Sites

Let customers create their own “shop front” focusing on their interest

Adjust appearance (eg, for visually disabled, or strict Muslims)

Doable, not huge success


Personalised Pricing

Companies would love to be able to charge people different amounts for the same product» Airline seats, cars, etc» Full price for people who are keen, in a

rush, don’t care about money» Discount for choosy/finicky


Personalised Pricing

Amazon, etc have tried this, but customers hated it.

So has gone “underground” for now. Technology permits this, but society’s

expectations does not allow it


Advertising

E-Shops (and other sites) can make money via advertising» Google makes billions from its “sponsored

links”» Amazon has adverts as well


Web Advertising

Conventional advertising focuses on visual appeal

Less successful on web» Flashy animated banner adverts are a

nuisance and distraction


Targeted adverts

Web allows relevant adverts to be associated with a web page» Google sponsored links based on search» Amazon could display different adverts for

sci-fi and romance novel Very effective if done well

» So Web sites can charge more for targeted adverts


Web adverts

Initially treated like TV adverts, put huge effort into flashy multimedia banner ads

Now focusing on simple targeted adverts instead

Advertising models cannot be blindly moved from TV to web» need new models!


E-Commerce Summary

Initially tried to make e-shops similar to high street shops. But» Need different business model» Trust issues much more important» Need appropriate legal framework


E-Commerce Summary

Sometimes technology really helps» Recommender systems, targeted adverts

Sometimes technology works but society doesn’t like it» Differential pricing

Dr. Ehud Reiter, Computing Science, University of Aberdeen1 E-Commerce – customer focus l...

Documents

Transcript of Dr. Ehud Reiter, Computing Science, University of Aberdeen1 E-Commerce – customer focus l...