25 posts tagged with "marketing"

In today's consumerist society, advertising is ubiquitous. Although the forms of advertising have changed significantly over the past century, its ultimate goal remains the same: to capture the public's attention and successfully sell products.

Selling Attention​

In the early 18th century, most advertisements were merely informative and did not aim for eye-catching effects. This began to change when Benjamin Day launched his own newspaper in 1833. To attract more readers, he priced his newspaper at one cent while his competitors charged six cents. With the newspaper's success, losses were inevitable. To increase profits and reduce losses, Benjamin started inviting advertisers to place ads in his newspaper and charged them for it. Ultimately, his publication achieved great success, making the world gradually aware of the value of selling attention.

Advertising Methodology​

By the 20th century, advertising began to take shape as a systematic field and was regarded as a science. An advertisement could be crafted to grab attention. Creating demand is one of many scientific methods. This method involves heavily promoting a problem that the public is either unaware of or that is entirely fabricated, and then claiming that a certain product can solve this problem. Additionally, advertisers in the 1920s realized that word of mouth could also be shaped by establishing and popularizing a brand.

Forms of Advertising​

Before the 1920s, advertising was primarily focused on public spaces. However, shortly thereafter, radio advertising became extremely popular. Advertisers were eager to sponsor radio content just to hear their names mentioned during broadcasts—because this would immediately attract a large audience's attention. Later, television quickly replaced radio as the dominant medium for advertising, becoming a more effective way to capture attention, a trend that continues to this day.

The rise of the internet ushered in a new wave of advertising revolution, with email emerging as a new form of advertising. A survey in 1973 showed that emails accounted for 75% of traffic on the internet. Emails are highly effective because they feel like a reward or incentive for customers—receiving an email feels good. Meanwhile, search engines like Google gradually became important resources for capturing user attention. To monetize attention, Google's founders introduced the Adwords advertising tool: it displays relevant ads alongside search results based on user queries.

Acquisition Efficiency Problem：How to achieve a better ROI in advertising?​

In details, Lyft's advertisements should meet requirements as below:

1. being able to manage region-specific ad campaigns
2. guided by data-driven growth: The growth must be scalable, measurable, and predictable
3. supporting Lyft's unique growth model as shown below

However, the biggest challenge is to manage all the processes of cross-region marketing at scale, which include choosing bids, budgets, creatives, incentives, and audiences, running A/B tests, and so on. You can see what occupies a day in the life of a digital marketer:

We can find out that execution occupies most of the time while analysis, thought as more important, takes much less time. A scaling strategy will enable marketers to concentrate on analysis and decision-making process instead of operational activities.

Solution: Automation​

To reduce costs and improve experimental efficiency, we need to

1. predict the likelihood of a new user to be interested in our product
2. evaluate effectively and allocate marketing budgets across channels
3. manage thousands of ad campaigns handily

The marketing performance data flows into the reinforcement-learning system of Lyft: Amundsen

The problems that need to be automated include:

1. updating bids across search keywords
2. turning off poor-performing creatives
3. changing referrals values by market
4. identifying high-value user segments
5. sharing strategies across campaigns

Architecture​

The tech stack includes - Apache Hive, Presto, ML platform, Airflow, 3rd-party APIs, UI.

Main components​

Lifetime Value(LTV) forecaster​

The lifetime value of a user is an important criterion to measure the efficiency of acquisition channels. The budget is determined together by LTV and the price we are willing to pay in that region.

Our knowledge of a new user is limited. The historical data can help us to predict more accurately as the user interacts with our services.

Initial eigenvalue:

The forecast improves as the historical data of interactivity accumulates:

Budget allocator​

After LTV is predicted, the next is to estimate budgets based on the price. A curve of the form LTV = a * (spend)^b is fit to the data. A degree of randomness will be injected into the cost-curve creation process in order to converge a global optimum.

Bidders​

Bidders are made up of two parts - the tuners and actors. The tuners decide exact channel-specific parameters based on the price. The actors communicate the actual bid to different channels.

Some popular bidding strategies, applied in different channels, are listed as below:

Conclusion​

We have to value human experiences in the automation process; otherwise, the quality of the models may be "garbage in, garbage out". Once saved from laboring tasks, marketers can focus more on understanding users, channels, and the messages they want to convey to audiences, and thus obtain better ad impacts. That's how Lyft can achieve a higher ROI with less time and efforts.

Customer Acquisition Efficiency Issue: How can advertising campaigns achieve higher returns with less money and fewer people?​

Specifically, Lyft's advertising campaigns need to address the following characteristics:

1. Manage location-based campaigns
2. Data-driven growth: growth must be scalable, measurable, and predictable
3. Support Lyft's unique growth model, as shown below:

The main challenge is the difficulty of scaling management across various aspects of regional marketing, including ad bidding, budgeting, creative assets, incentives, audience selection, testing, and more. The following image depicts a day in the life of a marketer:

We can see that "execution" takes up most of the time, while less time is spent on the more important tasks of "analysis and decision-making." Scaling means reducing complex operations and allowing marketers to focus on analysis and decision-making.

Solution: Automation​

To reduce costs and improve the efficiency of experimentation, it is necessary to:

1. Predict whether new users are interested in the product
2. Optimize across multiple channels and effectively evaluate and allocate budgets
3. Conveniently manage thousands of campaigns

Data is enhanced through Lyft's Amundsen system using reinforcement learning.

The automation components include:

1. Updating bid keywords
2. Disabling underperforming creative assets
3. Adjusting referral values based on market changes
4. Identifying high-value user segments
5. Sharing strategies across multiple campaigns

Architecture​

Technology stack: Apache Hive, Presto, ML platform, Airflow, 3rd-party APIs, UI.

Specific Component Modules​

LTV Prediction Module​

The lifetime value (LTV) of users is an important metric for evaluating channels, and the budget is determined by both LTV and the price we are willing to pay for customer acquisition in that region.

Our understanding of new users is limited, but as interactions increase, the historical data provided will more accurately predict outcomes.

Initial feature values:

As historical interaction records accumulate, the predictions become more accurate:

Budget Allocation Module​

Once LTV is established, the next step is to set the budget based on pricing. A curve of the form LTV = a * (spend)^b is fitted, along with similar parameter curves in the surrounding range. Achieving a global optimum requires some randomness.

Delivery Module​

This module is divided into two parts: the parameter tuner and the executor. The tuner sets specific parameters based on pricing for each channel, while the executor applies these parameters to the respective channels.

There are many popular delivery strategies that are common across various channels:

Conclusion​

It is essential to recognize the importance of human experience within the system; otherwise, it results in garbage in, garbage out. When people are liberated from tedious delivery tasks and can focus on understanding users, channels, and the messages they need to convey to their audience, they can achieve better campaign results—spending less time to achieve higher ROI.

The Vast Differences Between Western and Chinese Marketing Markets​

Region	China	West
Channel Granularity	Highly concentrated on platforms of giants like BAT	Fragmented across multiple channels
User Data Intelligence	Comes from a single closed-loop data source, where one company can control all aspects of personal data	Comes from dispersed data sources, with data on daily life held by different companies
Market Focus	Mobile, with 90% of purchases during Double Eleven coming from mobile	A wide variety of channels: TV, email, magazines, radio, billboards, newspapers, websites, etc.
Pace	Fast, optimizing revenue	Slower, optimizing profit

How Western Marketers Can Learn from Their Chinese Peers​

1. Build good relationships with major companies like BAT
2. Prioritize mobile
3. Embrace all-in KOL-driven viral marketing on social networks
4. Focus on content marketing rather than simple promotions and collaborations
5. Manage multiple channels in the West while navigating large companies' multi-platforms in China
6. Balance "thoughtful planning" with "plans not keeping up with changes"

What is change aversion?​

By and large, anytime you change what people regularly use in a product, they will always throw an uproar. This happens to almost every release of products like Gmail, YouTube, iPhone, etc.

How to avoid or mitigate change aversion?​

1. Let users understand, in advance and afterward. Warn them about the significant changes early and communicate why those places changed. Provide transition instructions afterward.
2. Let users switch. Don’t shut the door and leave them alone in the helplessness.
3. Let users give feedbacks and follow through.

Change Aversion isn’t an Excuse​

The product changes may turn out to be good or bad ones.

KYC (Know Your Customer) is Not Easy​

==How often do you get the chance to hear your customers describe the problems they face?== If you are an employee in a large company outside the marketing department, the answer is likely never.

Of course, if you do get the chance, it’s important to know that there are two very crucial parts to the ==core concept of buyer persona==:

1. Asking exploratory questions
2. Listening

==KYC (Know Your Customer)== is not easy. For example, in 2008, the sales of the iPhone 3G in Japan were poor. Japanese consumers were accustomed to recording videos with their phones and paying with debit cards or train passes.

Just Having a Buyer Profile is Not Enough​

A typical buyer profile cannot accurately inform marketers about the buyers' decisions to purchase. Marketers often make guesses based on demographics (such as age, income, marital status, education) or psychographics (personality, values, lifestyle, opinions).

Nonetheless, buyer profiles can provide some obvious answers. For instance, reaching out to a Chief Financial Officer (CFO) via email is quite challenging. Moreover, emphasizing the spaciousness of a car's cargo area, even if it can fit a large dog, is pointless for a woman who only has time to care for a goldfish.

The most effective way to build buyer persona models is not through guessing, but by researching those who have weighed their options, considered or rejected proposed solutions, and made decisions similar to the ones you want to influence.

Buyer persona = buyer profile (who will buy) + buyer insights (when/how/why they buy)

KYC is not easy​

==How often do you have an opportunity to listen to your customers describe their problems?== The answer is probably NEVER if you are an employee positioned in a non-marketing department of a large company.

If you do have the chance, two things lie at the core of the ==buyer persona concept,==

1. asking probing questions
2. listening

==KYC (knowing your customer)== is not easy. e.g. iPhone 3G was not selling well in Japan in 2008. Japanese customers were accustomed to using phones to shoot videos / pay with debit card chips / train pass chips.

A buyer's profile is good but not enough​

A generic buyer profile cannot make marketer understand exactly what determine’s the buyer’s buying decision. Marketers are just guessing based on demographics (age, income, marital status, education) or psychographics (personality, values, lifestyles, opinions).

The buyer profile can still give some obvious answers though. e.g. reaching CFO via an email campaign is so difficult. Emphasizing the spaciousness of the car’s cargo for a large dog is not useful for a busy woman that only raises goldfishes.

Rather than guessing, the most effective way to build buyer personas is to interview buyers who have previously weighed their options, considered or rejected solutions and made a decision similar to the one you want to influence.

Buyer persona = buyer profile (who will buy) + buyer insights (when/how/why to buy)

• CAC (Customer Acquisition Cost): Customer Acquisition Cost refers to the cost of getting customers to purchase a product or service.
• LTV (Customer Lifetime Value): Customer Lifetime Value is the net profit we can obtain from a customer.
• PBP (Payback Period): The payback period for capital investments refers to the time required to recover the investment cost or reach the break-even point. An ideal payback period is about one year.

LTV:CAC Ratio​

The LTV:CAC ratio helps you determine how much you should spend to acquire a customer for sustainable growth.

1. 1:1 = The more you sell, the more you lose.
2. 3:1 or higher = Good.
3. 5:1 or higher = Insufficient marketing investment.

• CAC: Customer Acquisition Cost is the cost to convert a customer to buy a product/service.
• LTV: Lifetime Value is the estimated net profit we can make from a customer.
• PBP: Payback Period in capital budgeting refers to the period of time required to recoup the funds expended in an investment, or to reach the break-even point. An ideal PBP is about 1 year.

LTV:CAC Ratio​

LTV:CAC Ratio helps you determine how much you should be spending to acquire a customer, so that you can achieve sustainable growth.

1. 1:1 = lose money the more you sell
2. 3:1 or better = good.
3. 5:1 or higher = under-investing in marketing

For high tech, we can define a market as

1. a set of actual or potential customers
2. for a given set of products or services
3. who have a common set of needs or wants, and
4. ==who reference each other when making a buying decision.==

Point 4 is the insight here - referencing each other is key to the marketing success. If two people buy the same product for the same reason but have no way they could reference each other, they are not part of the same market. They are in different ==market segments==.

The definition of a high-tech market is

1. Existing and potential users
2. Who have a demand for a certain type of product or service
3. And
4. These individuals reference each other when deciding on the products to purchase

The understanding of the fourth point is - mutual referencing is the key to market success. If two people buy the same product for the same reason, but they have no way to reference each other, they are not in the same market. They are in different market segments.

Is the innovation disruptive?​

Dsruptive innovation vs. Continuous innovation

• Whether it ==changes our current mode of behavior== or to ==modify other products and services we rely on==.
• Between continuous and discontinuous lies a spectrum of demands for behavioral change.

High-tech industries introduce disruptive innovation routinely, during which people are converted into customers by following a pattern of normal distribution. The product's user growth follows an S-curve.

When will people buy a high-tech product?​

Disruptive innovation's customers are converted at different stages in ==the technology adoption life cycle==. They are...

1. Innovators
2. Early adopters
3. Early majority (pragmatists)
4. Late majority (conservatives)
5. Laggards

Segment	What They Want
Innovators	novel, cool and experimental things
Early Adopters	gaining advantages or getting products before others
Early Majority	proven ROI, instant access, low transition costs, support available
Late Majority	adopting as minimal as possible or only when everyone else has adopted
Laggards	avoidance to adopt new things

What is the high tech marketing model?​

This cycle provides guidance of the ==high tech marketing model: the way to develop a high-tech market is to work the curve left to right, focusing on each group one by one,== because groups on the left promote products for the right ones in a momentum.

Momentum is vital because it can

1. save costs
2. make it fast so you won’t miss the window of opportunity before next disruption or competitor

Where is the CHASM?​

Inspecting into the technology adoption lifecycle, we can see

• two cracks

  1. Beneficial usage crack between innovators and early adopters. E.g., Esperanto, VRML, second life, 3D printing. To cross this, we need a flagship application.
  2. Competent majority crack, between early and late majorities. E.g., home automation.scanning and project management software. To cross this, we need to make it easier to adopt.

• and one CHASM

  1. Early adopter-to-majority chasm. Because their needs are different

     1. Early adopter is buying a change agent - they expect to get a jump on the competition. Having bugs is fine.
     2. The pragmatic early majority is buying a productivity improvement. They want technology to ==enhance, not overthrow, the established ways of doing business==.

  2. The compatibility above leads to two key points

     1. early adopters do not make good references for the early majority
     2. And because of the early majority’s concern not to disrupt their organizations, good references are critical to their buying decisions.

  3. Who did fall into the early adopter-to-majority chasm in 2014? E.g., holograms, pen-based tablets, fuel cells, QR codes (in the US), Massive Open Online Courses, Segways, Motorola iridium.