Hightech_marketing_1_Introduction.pdf

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Ⅰ. Introduction
High-tech marketing

1. Introduction
 Why algorithm marketing?
 The history of marketing can be viewed as the evolution of principles, techniques,
and best practices for a certain kind of business optimization.
 It has always been recognized that this optimization problem can be approached in a scientific way
and that rigorous mathematical methods can be applied to a wide range of marketing applications.
 Adopters of such methods, however, traditionally struggled with challenges related to
incompleteness of data, complexity of reallife marketing settings, inflexibility of business processes,
and software limitations.
 The challenges were especially overwhelming in areas that required far-reaching strategic decisions,
where human judgment was often the only viable solution for practical applications.

1. Introduction
 Why algorithm marketing? (Cont.)
 The advancement of digital marketing channels changed the game and created an environment that
requires millions of micro-decisions to be made, which simply cannot be done efficiently without
intelligent marketing software and algorithms.
 Targeted sales promotions, dynamic pricing in brick-and-mortar and online stores, e-Commerce
search and recommendation services, online advertising – all of these applications require advanced
methods of economic modeling, data science, and software engineering to realize the potential of
the digital environment.
 For instance, this potential cannot be fully achieved without tailoring personalized experiences for
millions of individual customers, which, in turn, requires millions of unique decisions to be made.
 This environment introduces the challenge of building marketing systems that make decisions and
act at an unprecedented level of autonomy, scale, and depth of analysis.

1. Introduction
 The subject of algorithmic marketing
 One of the traditional definitions of marketing describes it as the activity of defining products and
services offered by a company and communicating them to existing or potential customers.
 This activity can be broken down into several streams that are typically described as variations of the
following categories.
- Product : analysis of marketing opportunities, planning of product lines and product features,
assortment planning.
- Promotion : all methods of communication between the company and its customers:
advertisements, recommendations, customer care, and others.
- Price : pricing strategies, including posted prices, price discounts, and price changes over time.
- Place : historically, this refers to the process of making a product or service available to the
end user through various distribution channels.

1. Introduction
 The subject of algorithmic marketing (Cont.)
 The subject of algorithmic marketing can be better understood by distinguishing the following two
aspects of marketing activities: strategy and process.
 We use the term strategy to label long-term top-level business decisions that define the value
proposition of the company and set the overall direction for its marketing processes.
 The process is an implementation of the strategy that focuses on tactical decisions that support
continuous functioning of the company.
 The short summary is that the subject of algorithmic marketing mainly concerns the processes that
can be found in the four areas of the marketing mix and the automation of these processes by using
data-driven techniques and econometric methods.

1. Introduction
 The definition of algorithmic marketing
 We define algorithmic marketing as a marketing process that is automated to such a degree that it
can be steered by setting a business objective in a marketing software system.
 This implies that the marketing system should be intelligent and knowledgeable enough to learn
from the results to correct and optimize the actions

1. Introduction
 Historical backgrounds and context
 There is no sharp boundary between algorithmic and non-algorithmic marketing.
 However, it is evident that the level of marketing automation differs sharply across industries, which
indicates that some environments are more favorable in that regard than others.
 Let us briefly review several business cases that laid the foundation for algorithmic marketing in
search of the patterns and characteristics that enabled the systematic approach.

1. Introduction
 Historical backgrounds and context (Cont.)
 Online Advertising: Services and Exchanges
- The history of internet advertising can be traced back to May 3, 1978, when the first spam email was sent to
400 users of the computer network ARPANET, deployed at that time in just four locations: the University of
Utah, UCLA, UC Santa Barbara, and Stanford Research.
- Fifteen years later, by 1993, when ARPANET had developed into the Internet and the spread of the Web
enabled multimedia websites, the market of banner ads appeared.
- This new market originally relied on direct selling of banner slots offered by website publishers to
advertisers, but this approach started to lose its efficiency very quickly when there was a surge in the
number of websites.
- DoubleClick, launched in 1996, offered a platform that enabled advertisers to run ad campaigns across a
wide network of websites, dynamically customize a campaign according to its performance, and measure
the return on investment.

1. Introduction
- The breakthrough happened in 1998 when the GoTo.com search engine introduced an automated auction
model with two innovative features:
• Advertisers could bid how much they would be willing to pay to appear at the top of the results for specific
search queries.
• Advertisers paid per click, not per impression.
- Google measured the click-through rate for each ad as a ratio between clicks and impressions, and the
expected revenue was estimated as
revenue = bid price x click-through rate
- click-through rates tend to be low for irrelevant ads, so even high budget advertisers were not able to clog
up the bandwidth.

1. Introduction
- We can conclude that one of the most prominent achievements of programmatic advertising is a framework
that enables owners of consumer bases to provide personalized marketing services to parties who are
limited in their ability to interact with consumers.
- The infrastructure that sits in between the publishers and advertisers is typically provided by an
independent party and includes the following:
• Advertising services that enable advertisers to run advertising campaigns using the publisher’s resources.
These services are typically used to connect multiple advertisers with multiple publishers and resemble a
marketplace where resources are sold and bought, often on a bidding basis.
• Data services that collect and store information about consumers, taking it from publishers, advertisers,
and third parties. Advertising services take advantage of this data to run ad campaigns and make real-time
automatic decisions on ads to be delivered.

1. Introduction
- It represents a multipurpose marketplace of services and data that connects actors from different
industries. The range of services offered by such a marketplace can go far beyond advertising, covering
areas like credit scores and insurance premiums.

1. Introduction
 Airlines: Revenue Management
- It opened the door for low-cost carriers, who pioneered simpler operational models, no-frills services, and
reduced labor costs.
- The advent of low-fare airlines was a growing threat to the major carriers, who had almost no chance to win
the price war. Moreover, the established airlines could not afford to lose their high-revenue business
travelers in pursuit of the low-revenue market.
- The solution was found by American Airlines. First, they recognized that unsold seats could be used to
compete on price with the low-cost carriers, because the marginal cost of such seats was close to zero
anyway.
- The problem, however, was how to prevent the business travelers from purchasing tickets at discounted
prices. The basic solution was to introduce certain constraints on the discounted offers
- After a few years of development, American Airlines released a system called Dynamic Inventory Allocation
and Maintenance Optimizer (DINAMO) to manage their prices across the board.

1. Introduction
 Airlines: Revenue Management
- The case of American Airlines was the first major success of a revenue management practice advance:
hospitality, car rentals, and even television ad sales.
- The success of revenue management in the airline industry is clearly related to the specific properties of the
inventory and demand in this domain:
• The demand varies significantly across customers, flights, and time: the purchasing capacity of business
travelers can be much higher than that of discretionary travelers, peak flights can be much more loaded
than off-peak, etc.
• The supply, that is, the available seats, is not flexible. The airline produces seats in large chunks by
scheduling flights, and once the flight is scheduled, the number of seats cannot be changed.

1. Introduction
 Programmatic services

1. Introduction
- We choose to define six major functional services that are relevant for a wide range of business-to
consumer (B2C) verticals: promotions, advertisements, search, recommendations, pricing, and assortment.
- The relationships between the six services we have defined, as well as their connections to the marketing
mix, can be established as follows:
• The primary purpose of promotion and advertisement services is to match customers with offerings and
convey the right message to them. The capability for identifying the right customers and offerings is the
keystone of this service group.
• The search and recommendation services solve the problem of finding the right products for a given
customer, which naturally complements the previous service group. The principal goal of these services is to
enable and simplify product discovery, which is related to the Promotion domains of the marketing mix.
• The goal of pricing and assortment services is to determine and optimize the set of offerings and their
properties, including price. This group mainly covers the Price and Product domains of the marketing mix.

1. Introduction
- The concept of the programmatic method accentuates the objective driven design approach, so we can
attempt to define a common framework by starting with the notion of the business objective.
• Since any automatic decision making is driven by data, the decision-making pipeline starts with data
collection. Examples of input data for most marketing applications include customers’ personal and
behavioral profiles, inventory data, and sales records.
• The raw input data often has to be transformed into well-defined features that can be fed into analysis
and decision-making algorithms. The reason is that programmatic services often rely on some measure of
similarity between entities like products or customers to learn the patterns and make decisions, which
requires the entities to be represented as comparable sets of attributes.
• The most important step in the programmatic pipeline is to evaluate how well different action strategies
fit the business objective. This generally requires the development of one or more models that consume a
candidate solution and produce signals that indicate the level of fitness.

1. Introduction
• The signals generated by models carry information about the quality of different decisions that a marketer
can make.
• Finally, the feedback collected from the execution channels can be routed back to the models and
optimization procedures to learn from the results and adjust the decision-making logic.
- The programmatic infrastructure can support this by providing capabilities for market opportunities
analysis and global resource allocation that help to elaborate the objectives and parameters for individual
services, as well as consolidate the measurements.

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