Presentation on theme: "1 CS5038 The Electronic Society 2. A Quick Overview of Electronic Retailing B2C Retailing: types and ways to succeed Consumer Categories Consumer Decision."— Presentation transcript:
1 CS5038 The Electronic Society 2. A Quick Overview of Electronic Retailing B2C Retailing: types and ways to succeed Consumer Categories Consumer Decision Criteria Online Purchasing Aids E-Tailing Business Models Click and Mortar Strategy E-tailing Problems The middleman problem: e.g. travel industry
2 Business-to-Consumer (B2C) Retailing Ability to create direct relationships with consumer without intermediaries like distributors, wholesalers, or dealers Brick-and-mortar = Traditional offline retailer Click-and-mortar = offline + online presence B2C Market success is derived from: Offering quality merchandise at good prices Excellent customer service Convenience Goods that sell well online Brand recognition and guarantees Digitized products – music, video, software Frequently purchased, inexpensive items Well-known items with standard specifications no need to inspect
4 Click and Mortar Strategy Channel: route to customer (through delares/vendors/re- sellers/dealers and distributors, or directly (own shop or web-site)) Channel Conflict: Any situation where channel members are antagonistic due to real or perceived differences in incentives, rewards, policies or support Levis stopped online direct sales, because distributors complained Selling off old stock directly to make room for fresh models may undercut dealers. Have to coordinate parallel channels of distribution, and coordinate marketing strategies e.g., car dealer network + online direct sales
5 Click and Mortar Strategy (B) Successful Strategies: Empower the customer – 24/7 service and information Store locators; Product information; Inventory levels Speak with one voice – integrate back-end systems Customer gets the same information through telephone or webpage Leverage the channels – use best channel for each part of business process E.g. order electronically; physical sales return.
Computing Science, University of Aberdeen 6 Customers are not all the same! l Consumer types »Individual consumers »Organizational buyers l Goal of shopping »Pragmatic: buy something useful, cheaply »Hedonistic: have fun l Personality »Impulsive buyers purchase quickly »Patient buyers make some comparisons first »Analytical buyers do substantial research before buying
7 Consumer Categories Michael De Kare-Silver 47% want to shop electronically 19% Social Shoppers: enjoy shopping 14% Experimenters: ready to try new things 17% Convenience: responsive to things which save time or make life easier 16% Value shoppers: will purchase where they see value 14% Ethical: will purchase provided it is honest and pc 20% Habit die-hards: stuck in their ways Shopping avoider Hunter gatherers enjoy comparison/ search New technologists because it's cool Warning: these statistics are probably out of date!
8 Diffusion of Innovation A widely-accepted picture of technology adoption Rogers, Everett M. (1962). Diffusion of Innovations, Glencoe: Free Press.
9 The Long (Fat) Tail J.K. Rowling Demand, in units J.R. Hartley A few big hits (green). A lot of stuff that sells poorly (yellow). But a lot of the potential sales (in the area under the curve) are yellow. Titles, ordered by sales, decreasing Trad. channel cut-off for viable stock E-commerce. cut-off for viable stock
Consumer Behaviour Prentice Hall, 2002
11 Purchasing decision-making model 6 major phases Need identification Develop Consideration Set Information search and evaluation of alternatives Choice Decision Configuration/Personalization Upgrade/Replacement Need to help the Consumer at each stage of this process Return to this later from market-research viewpoint
12 Consumers Decision Criteria 1.Value proposition customer service, better prices, higher quality 2.Personal service treat the customer as a unique individual 3.Convenience self-contained site that serves all customer needs 4.Other criteria service after the sale, online help, return policy. Advertisers try to Influence consumer decision Productsportfolio of items available Price of the products Promotion of products (ads & giveaways) Packaging and delivery.
13 Online Purchasing Aids Shopping portals Comprehensive portals - many different sellers & comparisons Shop.lycos.com Niche oriented - specialised line of products (dogtoys.com) Shopbots and agents Tools scout the Web for specific search criteria - Mysimon.com Business ratings sites Sites that rate e-tailers - Bizrate.com, Gomez.com Trust verification sites Evaluate and verify trustworthiness of e-tailers - TRUSTe Escrow services 3 rd party to assure quality and proper exchange Communities of consumers Epinions.comsearchable recommendations on products PriceGrabber.comcomparison shopping
One-to-One Marketing Build a long term association Meeting customers cognitive needs Customer may have novice, intermediate or expert skill E-loyaltycustomers 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…
Personalization 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 Can also take advantage of more of long tail Dont need to keep stock in same way as traditional shop Can do things like Print On Demand
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: Xs 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, religious consumers) Do-able, 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, dont care about money Discount for choosy/finicky
Personalised Pricing (B) Amazon, etc have tried this, but customers hated it. So has gone underground for now. Technology permits this, but societys expectations does not allow it
Computing Science, University of Aberdeen 24 Advertising l E-Shops (and other sites) can make money via advertising »Google makes billions from its sponsored links »Amazon has adverts as well
Computing Science, University of Aberdeen 25 Web Advertising l Conventional advertising focuses on visual appeal l Less successful on web »Flashy animated banner adverts are a nuisance and distraction
Computing Science, University of Aberdeen 26 Targeted adverts l 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 l Very effective if done well »So Web sites can charge more for targeted adverts
Computing Science, University of Aberdeen 27 Web adverts l Initially treated like TV adverts, put huge effort into flashy multimedia banner ads l Now focusing on simple targeted adverts instead l Advertising models cannot be blindly moved from TV to web »need new models!
Consumer Satisfaction Prentice Hall, 2002
Customer Focus Summary Sometimes technology really helps Recommender systems, targeted adverts Sometimes technology works, but society doesnt like it Differential pricing Trust – sine qua non
30 E-Tailing Business Models (by revenue) 1.Subscription models Charge monthly or annual subscription fee for service 2.Transaction fee models Service fee based on the level of transaction offered 3.Advertising-supported models Charge fee to advertisers instead of customers 4.Sponsorship models Companies sponsor the business through donations (usually supplemental income) Alternative Classification (by service) Direct marketing – sell directly to consumers Pure-play e-tailers – do not maintain physical channel Traditional retailers with Web sites – 2 channels On-Demand Delivery Services (ODDS) Firms that have a fleet to deliver direct to consumers
31 E-tailing Failures and Lessons Learned Profitability – Each additional sale must lead to additional profits if it doesnt make cents it doesnt make sense Some pure play e-tailers lose money on every sale to grow to profitable size and scale Branding – drive to establish brand can lead to excessive spending Strategy based on assumption that they will get quick customer recognition Performance Web sites need to function in a fast, user-friendly manner Security (well return to this later) Static design or dynamic sites – rich databases of useful information encourage customers to return Incorrect Revenue Model – many were relying on advertising. Lack of funding – takes time to acquire sufficient customer base, investors were not willing to wait / take the risk First-mover may make mistakes, second-mover can learn
32 Middleman Problem (a case study in the travel industry) Retailers are middleman between provider and customer Traditionally make money by mark-up Buy product from supplier for £10, sell it to customer for £15 Difference (£5) is profit margin
33 Middleman problem Competition keeps profit margin down If you have a £5 mark-up, customers will go to competitor with £4 mark-up Suppliers may sell direct to customer If supplier sells product to customer for £12, he and customer benefit Disintermediation Hard to make money by mark-up in e-Commerce.
34 Example: Flights Pre-Internet, airlines sold flights to consumers via travel agents. Travel agent charged £100, gave airline £80 and kept £20 as mark-up If customer bought directly from airline, would be charged £100 (same as from travel agent) How did agents add value?
35 Example: Flights In Internet age, airlines sell flights directly to customer Airline sells flight to both customer and travel agent for £80. If travel agent sells flight to customer for £80, he wont make any money If travel agent charges £100, customer will buy direct from airline for £80 How can travel agent make money in Internet age? Especially a small one, not Expedia
36 Business Models Sell extras, upgrades: Sell flight at cost price, but extras at high markup E.g., insurance, delivery Use loss leaders and technology lock-in, e.g. Make sales elsewhere Sell advertising space on website Sell customer data. Address niche market Specialize in travel to, say, Poland Flights, hotel, airport transfer, tours Specialize in selling flights to universities Failures from poor understanding of niche, e.g. ``Pink it, Shrink it In these cases, how is value added?
37 Business Models (B) Branding Build up a good reputation, so customers trust you to offer OK deals, good delivery If youre trustworthy and cheap enough, it is not worth the hassle of looking at competitors Satisficing Means trusted shop can charge a bit more Marketing helps branding Customers visiting site helps Even if no purchase, just looking
38 Business Must Change Successful Internet travel agents differ from successful pre-Internet travel agent Old: small shop selling generic flights to local customers with high mark-up Joes travel agency Wheres the added value for the custommer? New: focus on product niche, high mark-up extras, advertising revenue, brand Expedia, escape2poland.co.uk Wheres the added value for the customer?
39 Internet Business Model Internet requires new business model(s) Management issue (mostly), not technology But must be resolved in order for e-commerce to really take off Poor business models one cause of dot-com boom/bust Pouring in money before business model issue resolved is a mistake!
E-Commerce Bus. Mod. 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
41 Organizational Change Internet (and most new tech) cannot be fully exploited unless society changes Change is painful for companies Many bankrupt small travel agents Many bankrupt dot-com investors
42 Organizational Change Change is painful for individuals Loss of skills: Joe has worked for 30 years selling generic hols to Spain, does this well Must ditch this, learn new skills Dislike model: Joe dislikes encouraging customers to buy overpriced insurance Loss of income: average income of travel agents may go down, even if they adapt
43 Summary Consumer Categories – value shoppers, convenience shoppers Consumer Decision Criteria – value, service, convenience Online Purchasing Aids – portals, shop-bots, trust sites E-Tailing Business Models Click and Mortar Strategy E-tailing Problems – channel conflict, wrong revenue model Case study from Travel Industry Need for organizational change
E-Commerce in the News OFT details widespread ongoing problems with compliance with UK Distance Selling Regulations ``More than a third of the UK's top online retailers could be breaking consumer laws, the Office of Fair Trading (OFT) has said. 2_Websweep_report_2012.pdfhttp://www.oft.gov.uk/shared_oft/research/OFT145 2_Websweep_report_2012.pdf Facebook pays £ in (corporation) tax in the UK despite advertising revenue of £ (estimated). Only reports £ revenue in the UK. 44