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1
MSc International Business Programme
International E-Business 2014
Lecture 10:
Pulling it all Together: ImplementationEconomic, and Organizational
Aspects of E-Business; Future Directions for e-business
2
Learning Objectives
• Assess development of e-commerce and migration to e-business• Evaluate the issues involved in global e-commerce (EC)• Evaluate potential migration strategies for market-facing
enterprises• Identify the major impacts of Web-based economics• Understand how we assess the performance of websites (Use of
KPIs)• Describe the major components of Web-based economics• Analyse the impact of online markets on competition• Describe the impacts on industry structure of intermediation, etc• Distinguish the trade-off between Richness and Reach• Describe the role and impact of virtual communities• Analyse the impact of EC on small businesses• Understand the research opportunities in e-commerce• Describe the factors that will determine the future of EC• Do some crystal-ball gazing …
3
Recommended Reading
• Schneider (2013): Chapters 11 & 12.• Chaffey (2011): Chapters 11 and 12• Jelassi and Enders (2005): Strategies for e-business Part III• Turban et al (2011): Business Intelligence, 2nd Edition• Beynon-Davies, P (2005): e-business• Laudon & Traver (2004): Chapters 12 -14• Siegel, D (1999): Futurize your Enterprise, New York, Wiley.
[now rather old-fashioned] • Papows, J P (1999): Enterprise.com, London, Nicholas
Brealey Publishing Ltd.• Evans, P and T S Wurster (2000): Blown to Bits, Boston,
Massachusetts, Harvard Business School Press.• Kalakota R and M Robinson (2001): e-Business 2.0, Boston,
Addison-Wesley (rather dated, but still relevant)
4
Where do we stand at present?
1993 2014
2001
Old World (supply-driven) New World (customer-led)19
95
1998
2000
e-business; m-commerce
2014
2005
bran
ding
e-commerceWeb 2.0
Web 3.0Web 4.0?
E-Commerce Phase 1 UP TO 2001 E-Commerce Phase 2 E-Com 3
5
2014 – What’s Happening?
Recent trends in the diffusion of ICTs 1. Fixed telephony penetration in decline: Many countries omit fixed telephone n/w
and move directly into Mobile Devices (e.g. Africa)2. The mobile revolution continues: Growth of 3G (and 4G) MAJOR impact worldwide;
Increased Use of Tablets and Smartphones: 3. Most Internet users are now in the developing world: Asia especially 4. Developing countries lag behind in terms of broadband connectivity 5. Monitoring the “digital divide”: Both Inter-country and intra-country1. Inequality is shrinking: slowly 2. Developments in country groups deserving special attention: BRIC (and VISTA):
BRIC Economies in the Doldrums3. No room for complacency: ICT badly affected by global recession
Addressing the broadband challenge: Uptake rapidly increasing 1. Reasons to promote broadband connectivity: Bandwidth; increased demand for video, audio
and collaborative applications; growth of “Cloud” 2. Policy options: Differ according to stage of development 3. Exploring the wireless broadband option: large impact of iPhone/iPad; Android 4. International connectivity challenge: problematic in many countries Future outlook and implications of the financial crisis: Who can say? http://www.unctad.org/
6
UNCTAD View (2)
Measuring ICT use and business performance: Critical Issue1. Most studies show positive impact of ICT use on economies 2. More capacity-building needed to improve ICT data situationWide gaps prevail in ICT use between and within countries 1. Large enterprises use more ICT: but SMEs key to growth 2. ICT use is mostly higher in urban than in rural areas (e.g. India)3. Sectoral differences in ICT use: Wide Disparities; “Digital Divide” 4. What do companies use the Internet for? Varies by country/typeImplications for National Economic and ICT policies 1. National ICT strategies: Many countries have them are they working2. Improving infrastructure in underserved areas 3. Creating skills – especially ICT skills: “Digital Divide” 4. Developing local content – requires multi-lingual sites 5. Strengthening the legal and regulatory frameworks – high priority
7
UNCTAD (3)
• Trade in ICT goods: Hit by recession; need Performance Improvement (worldwide). How do we measure e-perfomance: Web Analytics
• 1. Global shifts boost South-South trade: Good news for emergent nations: BRIC economies
• 2. A few economies dominate ICT goods and services trade: US, HK, CN, MY, IN, TW, SG, …
• 3. Reliance on ICT goods is high in some countries: US, etcSee: http://www.labs-associados.org/docs/OCDE_TIC.PDF
• 4. Shifts in the product composition: more mobile access • 5. Implications of the crisis: US and UK, plus EU countries with open
economies and highly developed financial sectors worst affected. EU: PIIGS economies; Asia (except JP) recovering fairly well.
• Offshoring and trade in IT and ICT-enabled services: Particularly IN • 1. Recent trends: Growing more slowly than forecast; PC sales falling • 2. How important is the quality of ICT infrastructure? Key Factor• 3. Implications of the crisis: a mixed picture worldwide
8
Analysing Web Performance
• Traditional management adage: You cannot manage what you do not measure.
• E-Business addendum: You cannot measure what you do not define
• In bricks-and-mortar businesses, senior managers have a number of fundamental metrics that reveal major trends, key opportunities, and hidden hazards.
• They can manage by numbers to plot strategy and navigate through unfamiliar and volatile business conditions.
• e-business managers are faced with unfamiliar and volatile business situations, while adopting new techniques like one-to-one personalization and viral marketing and have (until recently) comparatively vague measures for making decisions.
9
Some Metrics Problems
• What e-metrics are e-business managers tracking today?• What e-metrics and success-tracking techniques do these
managers expect to implement in the future?• Little detailed research, but NetGenesis (now defunct) discovered
• Web managers are inundated with data.• Web managers know the data contains immensely
valuable information.• Web managers are hampered in their desire to access
that information due to a lack of - • People. • Resources.• Standard definitions.• Domain expertise.
10
Research Findings
• “A lot of e-commerce companies just really don’t know how to measure their businesses right now. Nobody really knows because the industry is so new that there isn’t a standard of how to really measure your success and how to gauge your growth in the future. Is it going to be by your volume of ordering? Is it going to be by your repeat customers?”. . (Retail company)
• “The corporate organizations that could sort of ignore the Web have now realized that it’s creeping a little too close to the heart of their business, so they’re getting much more involved in the process” . . (Technology company)
• “Since I’ve got all these things I can measure, I’m paralysed by all the opportunities”. . (Service company)
11
What to Do? Analyse Web Traffic
• Are you attracting new people to your site?• Is your site sticky? Which regions in it are not?• What is the shape of your lead qualification funnel?• How proficient is your conversion of browsers to buyers?• What customer segments do you track?• How do these segments differ?• What makes them loyal?• How do you measure loyalty?• What attributes describe your best customers that can help you target
other prospects like them?• How can profiling help you cross-sell and up-sell?• What is your churn rate?• What site behaviour on your site indicates that a prospect is ready to buy?• What progression through sections of your site do you wish to encourage?• What is the optimal product assortment on a page?
12
Traditional Business Metrics
• Overall corporate value:• Market capitalization• Price-to-earnings ratio• Fixed assets
• Corporate process management:• Cash flow• Inventory turnover• Net profits• Customer turnover
• Financial expectations:• Market share• Book-to-bill ratios• Revenue per customer• Revenue per employee• Industry sector growth
Measuring e-business Performance
14
E-business: Fundamentally Different
15
Online vs. Offline Metrics
16
Implications for e-business
• E-business is real-time business and the indicators of marketplace trends are recorded as they happen.
• A banner ad placed on a portal site generates click-through statistics within seconds.
• An improvement in the navigability of your Web site instantly changes shopping cart activity.
• A press release that used to take weeks to have abarely perceptible effect on your company’s brand and bottom line now can impact your market’s propensity to buy within hours.
• Recent developments in BI and Integrated SIS mean companies can track performance in real-time
• Increasing use of the “cloud”: See documents on Canvas
17
Simple Approach: Assessing e-Marketing Campaign
www.crm-forum.com
18
Assessing Performance
• To understand how we can measure Customer response to marketing campaigns – via the Customer Life Cycle
• To gather an overview of the key metrics to be gathered, and what they mean to different business decision-makers
• Key metrics over the Life Cycle:• Reach • Acquisition• Conversion• Retention
• To appreciate the need to attract visitors to the business using various marketing programmes, entice them to perform some activities of value to the business, and get them to return frequently to re-purchase
• Best practice (Sterne, et al, 2007) indicates that developing an analytics focus around the customer life cycle is a purposeful and often very successful strategy: incresingly in cloud and SNS
Developmental Strategies
20
Customer Life-Cycle
Source: www.gartner.com
21
Life-cycle Framework
1. Provides a business-centric framework for understanding the contribution of website (and other channels) to business success• As more businesses move online, and become critical components of
larger multi-channel organizations, it becomes more important to have a common communication channel throughout the organization
• This is often referred to as “end-to-end” processing (information sharing)
• Research indicates that companies are working to integrate promotion and marketing in both on- and offline channels
2. Marketing analytics programmes will be significantly more successful if they conform to a defined framework – and the life-cycle model is ideally suited to this task• In the past, lots of data was collected, and then managers tried to
relate it to the business• Customer life-cycle approach allows us to generate reports that let the
company know answers to questions such as, “Our online marketing activities have helped us to acquire 20% more visitors month-over-month, and they are completing our key activities at a rate of 5%.”
22
Reach
• Reach: the likelihood or potential that you will be able to gain a prospective visitor’s attention
• Quantified as:• Number of people who see banner impressions served on a website• Number of people who search on a keyword that you have
purchased• Number of people who have seen an article written about your
company and products / services• Number of subscribers to a newsletter that you sponsor or
advertise in• Number of readers who subscribe to a newspaper or magazine that
you advertise in• Number of drivers who see a billboard advertising your company or
products• Number of viewers who watch a commercial that you run on TV• Number of recipients who receive an item of direct mail from you
… evidently each metric is both easy and impossible to measure accurately. How many people actively and actually read your message?
23
Acquisition
• Acquisition: measures how successfully your marketing activities convert the prospects’ visits into action
• That is, the proportion of visitors (to website) that click on a banner ad, an onsite link, a URL, or who actually buy something after entering your sales premises
• Some analysts argue that acquisition is best measured by arrivals and beginning activity of value
• Sterne (2007) takes the view that:1. Anyone who visits the website or offline channel after responding to
some type of marketing / advertising stimulus (treatment) is capable of completing an activity of value
2. In many cases, simple metrics are preferable to complex metrics, and it is often simpler to measure arrivals and activity rates.
• Acquisition statistics are primarily focused on the source of traffic – referring domains, search engines, keywords, etc
• Campaign analysis tools add richness to these and allow for qualification of visitors
24
Conversion
• Conversion and activities leading to conversion are important characteristics to capture from visitors
• Conversion Measures:1. Starting a download of information or an application2. Submitting information – lead generation3. Locating information – for example an FAQ list or support
document4. Navigating from general to more specific information5. Spending a defined amount of time online, or viewing a
specific number of pages6. Viewing key pages, such as Price Lists, product information or
service agreements7. Which objects (graphics, banner ads, etc) were viewed, and for
how long8. Which pages were NOT viewed. [needs to be analysed]
25
Conversion (2)
• Three essential considerations:1. Develop Analytics programmes such that you are able to
measure 3 or 4 “key” conversion rates – and monitor these closely. [These will differ according to each organization’s business model, but are essential to performance indication and evaluation]
2. Do not compare your rate to published rates, even those of direct competitors – ensure that your rates are appropriate to your own business
3. Use conversion rates to drive action and decision-making in your analytics programme. Conversion rates are an easy-to-understand metric, indicating whether a marketing campaign was successful, or not.
26
Conversion Rates: Warning
• Conversion rates need to be kept hidden from competitors. (why?)
• Do not publicise conversion rates to press or trade analysts (why?)
• All that others need to know about your business success is an estimate of your monthly web traffic (online) or footfall (offline) – available through ComScore and ….. And your conversion rate. With this information, and knowing your average order size, and competitors can accurately estimate your monthly revenue streams.
See: www.comscore.com
27
Retention
• Many studies assert that repeat Customers are more valuable than first time customers
• See http://www.newgistics.com/downloads/nl/0502/LoyaltyCorner.html
• Long-run effects of promotion depth on new versus established customers: three field studies. Publication Date: 01-JAN-04 (a little dated) Publication Title: Marketing Science
• Problems: How does one actually get Customers to become repeat buyers?
• How much loyalty is there in competitive markets – especially on the WWW?
• A product sold today may be cheaper from a competitor next day
Attrition Rates of Site Visitors
29
Life-Cycle and Analytics
LifeCycle and Analytics
Need to consider Analytics and Customer Life Cycle jointly:Good, effective analytics helps business “know its Customers”more completely, and acts as a source of sustainable competitive advantage; especially important in long-run
30
Customer Management Process
31
Metrics: Reach
• Difficult to measure on www, compared to offline• Offline, measure footfall, relatively quick and easy• http://moneyterms.co.uk/footfall/• Online, marketers try to buy advertising that is intended to
reach the largest number of people expected to respond to marketing / branding message
• Need to show messages with “correct” frequency• Problem with translating traditional advertising media
online: offline, buying media impressions; online buying “ad” impressions
• Offline information: Nielsen ratings; number of subscribers and demographics known
• Online: anonymous visitors, and accuracy difficult to measure
32
Pyramid Model of Data
Increasing value
Volume of available data
Hits: virtually useless
Page views
Visits
Unique visitors
Uniquely identified visitors
33
General Metrics
• Overall traffic volumes – not particularly useful in its own right, but as a guide to monitoring any changes in traffic patterns that may provide guidance on responses to changes and other decision-making
• Use “proxy” measurements – total page views• Break these down by day of the week, hour of the day, etc• Some analytics software packages will provide averages,
forecasts and drill-down capabilities to identify patterns, clusters and outliers
• Related metrics: referring sites • where visitors come from; IP addresses; URLs, etc• Visits: measured page views – which pages? how long?
what objects / information viewed? What objects clicked? etc
34
New Visitors
• Direct measure of efficacy of reach (“new, first time ever” visitors) and acquisition
• Often difficult where ISPs assign dynamic IP addresses• Dependence:
• How to determine newness and uniqueness of visitors?• Use cookies: simple text file sent to client machine by server• Even with cookies, difficult to tell if “new” visitor REALLY is
new to the site [Many people run maintenance software that empties cookies, caches and temporary files]
• Only sure way to identify newbies: persuade them to log in – often impractical
• Many authors reject using log-in strategies – seeing them as barriers to trade; many others reckon they identify REAL Customers (showing interest and initial commitment)
35
Ratio of New to Returning Visitors
• This is deemed a very good performance indicator (Peterson, 2007)
• New Visitors / Returning Visitors = Acquisition Mode• Need to ensure direct comparability between new and returning
visitors (over same period, day, time of day, etc)• Example (Peterson): Weekly data: 100 new visitors, 50 daily
returning visitors (summed over week) and 30 weekly returning visitors
• 100 new visitors / 50 daily returning visitors = 2.00• 100 new visitors / 30 weekly returning visitors = 3.33• Interpretation – these figures are significantly different, and
require different actions to be taken by marketers in analysing communication effectiveness.
36
Percentage of New Visitors
• “perhaps the best measure of how effectively [one] is able to reach people on the web.” (Peterson)
• Calculation: New Visitors / Unique Visitors• Many analytics packages will report different
types of visitor – daily, weekly, monthly, etc. Need to ensure comparisons are made of similar time period data
• Interpretation: straightforward – 30% means 30% of visitors were reached and attracted for 1st time ever. [good result for acquisition campaigns]
37
Entry Pages and Content
• Entry Page to website: first page seen by visitor on arriving at site.• Your landing pages may have only 8 seconds to capture the
attention of visitors and direct them toward their goal – to purchase, to get more detailed information, to move along a process. http://www.widemile.com
• Effective landing pages contain the following key elements:• Focused Content• Consistent Design (with clear navigation)• Analysis and Reporting (for the webmaster / marketers)
• Commonly believed that Home Page (index.htm) is the Landing Page (entry page)
• Research indicates that many search engine results take visitors to other pages in the website
38
Visitor Geographic Location
• How important?• Localised business: may provide useful localised info• National business: may identify regional demand
patterns: Opportunity to localise web site (language)• Global business: ABSOLUTELY CRITICAL TO SUCCESS
• Different Analytics packages provide information to different degrees of granularity
• http://akamai.com/en/html/services/edge_how_it_works.html• Monitor location to identify patterns / spikes in data• Identify key periods of year in different markets – pretty
obvious.• May need to “think global; act local” with targetted
campaigns, localised language, cultural overlays / attention to local issues and interests
39
Error Pages
• Often overlooked in analytics• Can provide focused view of strengths (and weaknesses) of web
presence• See http://www.w3.org/Protocols/HTTP/HTRESP.html• http://www.modemhelp.net/httperrors/httperrors.shtml
• Server logfile provides detailed information:• Code 100 – 101 – Information Codes• Code 200 – 206 – Success Codes• Code 300 – 307 – Redirection Codes• Code 400 – 417 – Error Codes (includes 404!)• Code 500 – 505 – Server Error Codes
• Most codes report URL and pages sought, time error occurred, and frequency of occurrence; enables site improvement and improved Customer service.
• Better Customer Service = Competitive Advantage
40
Interested Visitor Share
• Based on “committed visitor share” [Eisenberg and Novo, Guide to Web Analytics]• Calculation: Visits of more than n minutes / total visits• n is usually defined by the site owner• May be obtained from historical log files to estimate
average time on site• Lots of pitfalls: visitor goes to lunch; takes a break;
makes coffee, etc. Does this constitute a site visit?• Interpretation: depends on type of site, site goals and
objectives, type of online content, etc [entertainment, news, sport, educational, retail, FAQs – all have different patterns of visiting and online behaviours]
41
Campaign Reach Metrics
• Attempt to measure effectiveness of marketing campaigns• Impacts on every phase of the Customer Life Cycle• Need to know reach and frequency of each ad,
response rate for campaign (acquisition), conversion rate (retention and loyalty)
• Common measures:• Impressions served:
• Dependent on analytics package and type of impression to be measured
• Often measured by vendor serving the impressions (e.g running ads on a banner network, or purchasing search engine keywords for placement – Google or Overture)
• Also obtainable from server log
42
Impressions Served
• Key to calculating reach and overall campaign effectiveness• Not knowing how many people saw the ad or brand statements
makes it impossible to evaluate campaigns• Interpretation:
• Critical to measuring quality of opportunity to present marketing message
• Need to compare number of impressions served with total number of impressions purchased (or were promised by the ad agency)
• Open Rate: specific metric for e-mail marketing campaigns – % of mails actually opened
• Calculation: Unique Readers / Total e-mail Addresses• Address lists commonly purchased from agencies• Search on Google for e-mail marketing returned 501m results!
43
e-mail Marketing
• Often misunderstood as “spam”• Ethical e-mail marketing campaigns use “opt-in” lists of
addresses, to run effective campaigns• Sterne (2005): “e-mail is an effective message-testing tool.
While [it] may have used e-mail to drive web traffic and sales, [it] may not have been used as a tool for testing [the] brand message.”
• Not only good for testing brand strength, but also an effective marketing communications (marcoms) tool, and a component in driving continuous improvement processes on the website and in marketing focus / strategy
44
E-mail Marketing Metrics
• Total sends – pretty obvious
• Successful sends – non-returned
• Hard bounces – address no longer valid
• Soft bounces – undelivered due to server error (and out-of-office messages)
• Messages “Missing in Action” – trapped in transit
• Tracked opens – using impression measurement tool
• Estimated opens – subjective guess at % opened (unreliable)
• Tracked click-throughs – number of successful “clicks” recorded on links in e-mail
• Forwards and referrals – difficult to measure accurately
45
Example Performance Scorecard
Chaffey (for a retailer site) Numbers denote Chapters in Book
46
Measuring Acquisition
• “The closer the match between the capabilities of the website and the needs of Customers, the greater the likelihood of success in the [acquisition] stage [of the Customer life cycle.]”Hurol Inan, Measuring the Success of Your Website
• Acquisition: generally easier to measure than other KPIs.• Why? Because most of the necessary information is gathered by
the firm itself from its analytics activities and internal records• How many visitors are we acquiring?• Where are they coming from?• What do we know about their demographics?• What are they seeking onsite?
47
General Acquisition Metrics
• % New Visitors• Average number of visits per visitor
• Calculation: Visits / Total Visitors (must be > 1!)• If using segmentation tools, do this calculation for
different segments of visitors – new, existing, returning.• Dependence: measuring “visitors”
• lots of debate about this metric: length of visit (some say 30 minutes; others say 10 min.) Sterne, 2007
• Average Number of pages viewed• Calculation: Page Items / Visits (monitor continuously)• May also be segmented to identify differing patterns• “Depth” of visit – no. of pages visited, etc
48
Page “Stickiness”
• Measures how long the Landing Page engages visitor attention• Critical to evaluation of acquisition efforts• Also may measure “slippage” – how quickly visitor
leaves site, or goes back to previous page in browser cache.
• Calculation: Slip = Single access page views of page/ Entry page views of same page
• Stickiness = 1 – Slip.• Interpretation: If calculated stickiness for the Home
page is 0.45, only 45% of visitors went beyond the Home Pagein the time frame measured. Ideally, Home pages are intended to guide people to other pages and information on site. [Ideal stickiness: 70 – 80% is good]
49
Why Page “slip”?
• Pages slow to load• Too many graphics, Flash movies and no opt-out of
introductory pages (wearisome)• Poor fit between the message that prompted the visitor in
the first place and information on site• POOR PAGE DESIGN
• http://www.usability.gov/pdfs/guidelines.html• http://www.useit.com/• www.webpagesthatsuck.com/
• Misspellings and grammatical errors• Poor reach for marketing campaigns intending to generate
high traffic rates
50
Cost per Visitor
• Simple metric• Calculation: Marketing Expenses / Visitors• Problems:
• Separating Online Marketing expenses from overall marketing budget
• Much research on comparison of offline and online marketing, advertising and Customer service provision
• Student Activity: Do some web searches for quantitative information, research findings on cost of offline vs. online Customer service (try financial institutions sites)
51
Cost/Visitor & Related Metrics
• C/V obviously closely related to:• Sales / Visitor• Average Order Value• Site-wide (purchase) conversion rates [see later]• Ratio of New Visitors to All Visitors
• Also useful to identify “Heavy User Share” (Eisenberg, Guide to Web Analytics, 2004 – copy online on WebCT)
• Heavy User Share = Number of Visits to n or more pages / Total Visits
Eisenberg suggests setting n to 10 or 11, to capture “interested visitors” – who may be promising prospects for conversion to Customers
Also helps understand the quality of fit for the audience being currently attracted – possibly better qualified [MAN]
52
Top Pages and Content Requested
• Identify pages and content that New Visitors find most compelling. Eisenberg strategy advice:• Create a system to send cookie to visitors based on
number of visits they make• When visitor first arrives, check to see if cookie exists;
if not, assume “first time” visitor (possible problems?)• Allows analysis of potential goals of visitors – and
allows marketers to respond by “tailoring” information to visitors’ needs (using dynamic real-time website customisation: needs database integration and use of XML.
• Example: Amazon, Nike, other online retailers)
53
“Visit” Cookie Set-up
• Tracking acquisition and retention allows differentiation between new / existing visitors
• How? Set up and read cookies from visitor’s browser:1. Check to see if cookie already exists:2. If it does, identify number of visits and date/time of last 3. If not, write current date/time and number “1”4. If step 1 indicated existence, compare dates/times5. If number of minutes since last click 10 (or 30 …),
increase number of visits by 1, and write to logfile6. If < 10 (or 30), merely write date / time to cookie
• Repeat procedure for every visit (hourly, daily, weekly, etc) – Provides Frequency Information. Usually available directly from server logfile.
54
Average Time on Site
• More important to monitor this metric, than just calculating its value.
• If average “dwell” time is changing over time, in which direction is it moving?
• If decreasing, reasons need investigation.• If increasing, how can this trend be enhanced
and developed by further marketing activity: communications efforts; campaigns; brand development; strategic responses, … etc.
55
Content “Focus”
• Sterne and Cutler: e-Metrics: Business Metrics for the New Economy• Relates average number of pages visited in a content
area to total number of pages in section• Calculation: Content Page Views / Content Unique
Visitors• Then, Content Focus = (Av Number of Pages viewed per
visitor by content) / Total Number of Content Pages• Allows identification of wide and narrow visitor focus • Provides decision-makers with information on
appropriate responses to make to each (many?) type(s) of visitor
56
Performance Management System
57
Use of Google Analytics
http://www.google.com/analytics/
58
Campaign Types
• Fixed Delivery Cost• CPM (cost per 1000 impressions)• Banner Advertising• Advertising Partnerships (some)
• Variable Delivery Cost• Cost-per-Click (CPC)• Pay-per-Click (PPC)• Slightly trickier: need to total the sum for each day (or
other time period) of the campaign
• CPC and CPA: major factors in assessing the cost-effectiveness of marketing campaigns, and decision- making on campaign / media choices
59
Importance of Metrics and KPIs
• Failing to measure response to activities associated with website and e-commerce business aspirations is unforgivable
• Resources are (always) scarce, and need to be allocated and deployed effectively
• Obtaining the Key Metrics and KPIs is not too difficult, so you can analyse how successfully (or not) you are delivering what your target market requires
• Most Web Analytics software will deliver these results directly, and allow you to gain deep insights into what works – and what does not.
• See, e.g. Google Analytics; Google Adwords, etc• Coupled with BI and Integrated Information Systems offers
tremendous power to your efforts to succeed.
60
What are Markets for?
• Markets have three main functions• Matching buyers and sellers• Facilitating the exchange of information,
goods, services and payments• Providing an institutional infrastructure
• Electronic Marketplaces = “Marketspaces”• Increased effectiveness and reach• Lower distribution costs (maybe)• ‘Friction-free’ markets
61
Economics of Information and Economics of Things
• Are traditional and E-Business economics different?
• E-Biz involves gathering, selecting, synthesising, and distributing information
• Economics of E-Biz starts with supply and demand, and ends with pricing and beating the competition
62
Economics of Information
• NOT a fundamental or new body of economic principles
• BUT a rebalancing of existing economic forces• Taking particular account of un-gluing and
re-gluing within -• organisations • supply chains• value-chains• economic systems
63
Effects of Information
• Better information: may allow for better decision-making • Faster information: may allow more timely decision-making • More accurate information: may improve quality of decision-
making • Lower cost information: may encourage search for cost effective
decision-making • ALL aspects of information supply impact on economic
processes: • e.g. Health Care Industry in US
(one-third of cost = informational)• “Inventory is the result of information deficiencies."
(Michael Dell Dell Computer example)• 70% + of business decisions turn out to be bad decisions• How can we improve the quality of decision-making -
using web-based technologies?
64
Information and Things
Optimal
Physical Products Digital Products
Unit
Cost Unit
Cost
QuantityQuantity
65
Components of Digital (Virtual) Economies
• Consumers— people that surf the Web as potential buyers of goods and services
• Sellers— front stores available on the Net, advertising and/or offering millions of items
• Infrastructure Companies— companies providing the hardware and software necessary to support EC
• Intermediaries— intermediaries of all kinds offering their services on the Web
• Support Services— includes certification and trust, assures security to knowledge providers
• Content Creators— media-type companies create and maintain Web pages and sites
66
Digital (Information) Products
• Paper-based documents: books, newspapers, magazines journals, newsletters
• Product information: product specifications, catalogues, user manuals, tourism and leisure information, etc
• Graphics: photographs, postcards, calendars, maps, posters, x-rays, other images, etc.
• Audio: MP3, music recordings, speeches, lectures, industrial voices, podcasts
• Video: QuickTime, Real Player, Flash movies• Software : programs, games, development tools, agents,
recommendation engines
67
Digital Services
• Government services: forms, benefits, and welfare payments, licences, etc• Electronic messaging: letters, faxes, telephone calls, SMS• Business value creation processes: ordering (online procurement), bookkeeping, inventory movements etc• THE CLOUD• Auction, bidding, bartering, etc.• Remote education, telemedicine, other interactive services• Cyber cafés:interactive entertainment, virtual communities – MySpace, Twitter, FaceBook, LinkedIn, etc – becoming increasingly important.• Challenge: How to monetize Social Networking• S ee (e.g. http://mashable.com/2009/03/28/monetize-social-media/)
68
How do these affect our Business?
• Information is embedded in ALL business activities
• Competitive Advantage will accrue to the organisations that manage information most effectively
• Past business practice: trade-off between richness and reach
• Information, when separated from physical modes of delivery, allows organisations to develop increases in richness and reach SIMULTANEOUSLY
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Richness and Reach
• Trade-off Between Richness and Reach• “Richness”: quality of information
• As perceived by the user of the information:• Accuracy• Timeliness• Bandwidth• Relevance, etc.
• “Reach”: number of persons who participate in sharing the information
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Trade-Off
Richness
Reach
Evans P and T H Wurster (1997): “Strategy and the new economics of information”Harvard Business Review, Oct-Nov.
Traditionaltrade-off
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Richness and Reach Again
Richness
Reach
New levelsof attainablerichness andreach
Enablers:Connectivity explosionStandards dissemination
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Competition Effects
• Impacts on competition• Lower buyers’ search cost• Reduced Information asymmetries (important)• Speedy comparisons (of price and non-price)• Differentiation (segmentation)• Lower price (sometimes)• Customer service enhancements• Digital products lack normal wear and tear
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Internet Pricing
• Price Discovery• Electronic marketplaces enable new types of
price discovery – but NOT always offering lower prices than offline.
• Web-based auctions at Onsale.com and eBay.com
• Intermediaries such as Priceline (www.priceline.com)
• Intelligent Agents • (http://www.cs.cmu.edu/~softagents/ )
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Inhibitors: Internal Politics
• Implementation of Strategy Depends on Co-operation• COMMUNICATION (key)• LEADERSHIP• COMMITMENT OF TOP MANAGEMENT• COMMITMENT TO CHANGE (remove legacy effects)• VISION• COMMITMENT OF RESOURCES (human and £££)• CONSULT WIDELY (evaluate responses with care)• EVALUATE OUTCOMES … and COMMUNICATE!
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E-Business Blueprint
Objective
Time
2017
2016
2015
20142014
Today
Where do we need to be 3 years from today?
Work backwards
How to Plan & Implement?
• Information technology projects• Keys to successful implementation
• Planning and execution: 5Ps• Successful electronic commerce initiative
business plan activities• Identifying initiative’s specific objectives• Linking objectives to business strategies
• Setting electronic commerce initiative objectives• Consider strategic role of project, intended
scope, resources available
Identify Objectives
• Typical business electronic commerce objectives• Increasing existing markets’ sales• Opening new markets• Serving existing customers better• Identifying new vendors• Coordinating more efficiently with existing
vendors• Recruiting employees more effectively
• Objectives vary with organization size• Compare e-commerce risk to inaction risk
Link Objectives to Business Strategies
• Downstream strategies• Tactics to improve the value businesses
provide to customers• Upstream strategies
• Focus on reducing costs or generating value working with suppliers or inbound providers
• Web use for businesses• Attractive sales channel for many firms• Complement business strategies, improve
competitive positions
Link Objectives to Business Strategies (2)
• Third-wave e-commerce activities• Impacted by smart phones’ and tablet devices’
pervasiveness• Web access in many more locations• Changed nature of online communication
• Technology benefits more easily acquired• Example: Social media tools
• Smaller businesses’ electronic commerce activities increase anticipated
Identify and Measure Benefits
• Some electronic commerce initiatives• Obvious, tangible, easy to measure• Example: increased sales or reduced costs
• Other electronic commerce initiatives • More difficult to measure• Example: increased customer satisfaction
• Identifying objectives• Set measurable objectives
• Include intangible benefits
Identify and Measure Benefits (2)
• Using Web sites to build brands or enhance existing marketing programs• Set goals in terms of increased brand awareness
• Measured by market research surveys, opinion polls• Companies selling goods or services online
• Measure sales volume in units or dollars• Complicated to measure brand awareness or sales
• Increase due to other things company doing• Increase due to time or general improvement in the
economy
Measuring Benefits
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Managerial Issues
• Taking Stock: Strategy Development and Implementation• Ensuring the close alignment of Business and ICT strategies (Research
indicates this is critical to success: think back to the “dot bombs”, 2000-2001)
• Managing the Organisational Transformations• Value Chain Deconstruction, Analysis, Evaluation,
Innovation and Reconstruction • Managing the Organisation’s Knowledge and Wisdom
(both Tacit and Explicit)• Developing the Customer-focused Business• Encouraging a Market-Facing Enterprise• Supply Chain Integration: Disintermediation or
Re-intermediation?• Cooperative, collaborative e-commerce – involving Customers,
Suppliers and Sales Channels
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Managerial Issues (2)
• CPFR: see http://scm.ncsu.edu/scm-articles/article/introduction-collaborative-planning-forecasting-and-replenishment-cpfr-a-tu
• Online delivery of products and services • Industry Convergence (e.g. financial services)• Value Chain Extraction
(e.g. manufacturers monitoring their customers’ inventory levels)
• Value Chain Insertion (e.g. ISPs become integral part of their customers’ value creation activities)
• Changing Industry Concentration (M & A)• Product Transformation (from “products” to “services”)• Changing Geographical Distribution
(3 time-zone organisation)• Managing the Virtual Organisation
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Rapid Technological Innovation
Hardware Software Communications
CamerasSensorsDigital Versatile DisksMobile DevicesPersonal Digital AssistantsNetwork ComputersSmart CardsSmart TVs
Agent SoftwareBiometric SoftwareAudio/VideoData MiningDigital CashDigital SignaturesDirectory ServicesDistributed AuthoringEncryptionJava AppletsObject-oriented Technology“Push” SystemsReal-time MessagingClairvoyant Search Engines
Cable ModemsDSL AdaptersSmart PhonesVideoconferencingVoice/Data IntegrationWireless Data
… these predictions were made in 1996 (Tapscott)
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The Future?
• Entrepreneurial Management Revolution (read Siegel)• Corporate Vision is Customer-led• Organisations and Customers as “Partners”• M-business (expected to be HUGE, if we get G3/G4 right )• Biometrics: Already in widespread use: Expect more!• IP v.6: Run a test to see if you can access IP v.6• Internet2 [http://www.internet2.edu/about/ ]• Lifelong Phone Number• Wearable Computers• Intelligent Machines• Intelligent search: Web 3.0 (semantic web)• Web 4.0 …• The Truth Economy (Nike; Clinton, etc.)
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m-business (briefly)
• Use of wireless digital devices (cell phones; PDAs, hand-held devices to enable transactions on the Web)
• Most advanced examples: Japan, (DoCoMo; I-mode); Korea Scandinavia (especially Finland)
• Previous attempts: WAP using WML not very successful• G3 mobile phones and hand-held devices (iPhone, iPad,
etc) seen as the future “Killer Apps”• US lags behind Europe at present in mobile phones• m-commerce uses GPS (GPRS): where is GPS in Europe?• M-commerce business models under development:
(see my.mp3.com)• Location-based e-commerce: Cambridge Experiment
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The Future…?
• Who knows?• (weak) Consensus: consumer-centric markets
(the market-facing organisation)• Custom manufacturing
(mass customisation been in place for more than 7-10 years)• Dynamic Pricing (feasible - operational in some markets)• Instant fulfilment (maybe)• Greater use of intelligent agents
(price discovery; reducing information asymmetries)• 3-D Browsing (watch this space) 3-D Printers (make ANYTHING!)• Tactile computing? (data gloves; RFID; etc)• Internet Appliances and Internet-connected appliances• The Wired Home (already in prototype: Orange Phone)
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The Challenge …
“There is nothing more difficult to take in hand, more perilous to conduct, nor more uncertain
in its success, than to take the lead in the introduction of a new order
of things. For the reformer has enemies in all those who profit from the old order.”
Niccoló Machiavelli. [1532] “The Prince”
Try This …
• PERFORMANCE = ABILITY x ATTITUDE• Let A = 1, B = 2, C = 3, etc
ATTITUDE
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The Future …
Good Luck in your Careers!
Keep on Learning all your Lives
Keep an Open Mind
Embrace Change; Do Not Resist Change!
I wish you every success in your futures.
Travel safely!
Please keep in touch!