Software Engineering Daily

In the 1960s, advertising agencies were high-dollar creative producers. A client would come to an ad agency and pay millions of dollars for artistic messaging that would convince a consumer to buy a product.

How could you measure the success of these advertising campaigns? Maybe you could see success in the sales data. Maybe people were starting to talk about the product. Ultimately, success was defined by how satisfied the client was.

When it comes to measuring outcomes, advertising has always been a messy business.

Bob Hoffman’s long career in advertising included CEO positions at three different agencies. He helped huge brands craft their messaging, and grab consumer attention. In Bob’s world of advertising, lots of money was spent on creativity. Were the campaigns successful? That depends who you ask. In the old world of advertising, everyone acknowledged that success was subjective.

As human attention moved online, the world of advertising changed. Advertising began to move from TV and magazines to websites. Technology companies were formed to enable this new type of advertising–known as adtech. These companies claimed to bring scientific accuracy to advertising campaigns. The biggest adtech player was Google, who perfected search advertising.

If you could imagine the opposite of what Bob Hoffman built his career doing, it might look like search advertising.

Bob’s campaigns were about creating a brand’s voice, with colorful art and subtlety and ambient messaging. Advertising was about turning a brand into an entity you recognize, teaching the consumer to associate Nike with fitness, or Dove soap with clean hands, or Cheetos with cheesy, salty attitude.

Search advertising, on the other hand, is just text. You enter a search query, you are looking for black socks, and the top link that comes back is a line of text that says “cheap black socks.” Search advertising catches people who have an intent to do something. They have stated their intent by typing into a box. With search advertising, a brand might not even need a sexy, flashy creative.

The idea of intent-based advertising was expanded with retargeting. As you navigate through the internet, adtech companies are watching you, gathering data on your intent. Maybe you aren’t typing your desires explicitly into a search box–but you are clicking on articles and blog posts and tweets. With all your online interactions, adtech companies can figure out that you are looking for black socks whether you say so or not.

Money poured into adtech for very good reasons: intent-based marketing works. The shift to adtech put agencies in an uncomfortable position. If they couldn’t capture the advertising market by selling highly produced, unmeasurable creativity, they would have to make their money doing something else.

The situation was this: big brands like Procter and Gamble were buying most of their advertising through agencies. Procter and Gamble decided it wanted digital advertising. The adtech companies were the ones who knew how to produce and distribute digital advertising. Since agencies had the relationships with the big brands, and adtech companies had the technology, agencies began to partner with adtech companies.

This is actually a simplified version of what happens. Agencies subcontract advertising deals to digital agencies. A digital agency buys technology from a slew of adtech companies: some technology tracks users around the internet, some technology places bids on advertising spots that will land in front of users. Because of all the middlemen, the incentives are aligned against the brands.

Contrast this world of agencies and adtech companies with the world of Google and Facebook. They are a duopoly because they earned that position. By creating a single monolithic purchasing process, they have removed much of the risk that comes from a purchasing process stocked with middlemen.

But back to Bob Hoffman.

As money poured into adtech, user tracking, and Google, brands started to care more about metrics. When Bob met with a brand, the brand wouldn’t be asking about the cool new advertising campaign featuring a young actress drinking a Coca Cola. The brand would be asking about the click-through rate of a display advertising campaign.

Brands moved their focus to statistics, and away from creativity. And technology companies were happy to provide them with statistics. Whether those statistics were true or not is another story altogether. The industry was moving from creative BS to outright lying, and Bob decided to leave.

In today’s episode, Bob explains how the state of advertising became so problematic, and the ways in which it harms us Internet users.

We have done lots of reporting about advertising fraud for the last year, and it is a popular topic because people are often shocked to find that online advertising is inextricably linked to organized crime, surveillance, and Twitter botnets. That’s not to say that online advertising doesn’t work–it certainly does! But understanding the dark underbelly of the Internet’s cash cow is a necessary precondition to finding a solution.

To find all of our old episodes about ad fraud, you can download the Software Engineering Daily app for iOS and for Android. With these apps, we are building a new way to consume content about software engineering. They are open-sourced at github.com/softwareengineeringdaily. If you are looking for an open source project to get involved with, we would love to get your help.

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In America, the tech companies we focus on are commonly known as FAANG: Facebook, Amazon, Apple, Netflix, Google. We all know what these companies do because they impact our daily lives. In Asia, there are three giant tech companies that have similar scale: Baidu, Alibaba, and Tencent, otherwise known as BAT.

Technology within a location is shaped by the pressures of that location. You might think we live in a global society, but tech in Asia is dramatically different than it is in America. Differences in culture lead to differences in product development.

In China, a different political system contributed to more rapid adoption of online payments. Because there is more payment data, people can be given loans more efficiently. Less of the population is “unbanked.” Online payments are mostly handled by WeChat, a social networking product from Tencent, and Alibaba, an ecommerce giant. If you live in the West, imagine that Facebook and Amazon handled most of your payments for everything. You would have a different relationship with those companies.

Bernard Leong is the host of Analyse Asia, a podcast about Asian developments in technology in business. After studying materials science in Singapore and theoretical physics at Cambridge, he made his way into business and journalism, and developed an interest in the Singularity–a subject that few people took seriously until recently (one topic we explored in this show is Masayoshi Son, the Japanese tycoon who wants to invest nearly a trillion dollars into technology companies; Masayoshi believes firmly that the Singularity is coming).

Shenzhen: The Silicon Valley of Hardware (Full Documentary) | Future Cities | WIRED

In the Plex by Steven Levy

The Hidden Forces Behind Toutiao: China’s Content King

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Interviewing engineers is not a solved problem. Quite the opposite–everyone in the software industry will tell you their own personal issues with the hiring process.

One reason that technical interviews have not evolved significantly is the lack of standardized tooling. Some companies give you one phone screen, some give you two. Some companies have you solve brain teasers (“how many golf balls fit in a school bus”) and some make you fix bugs in their production codebase. During the on-site interview, some companies use whiteboards, some let you use a laptop.

Software companies do so much–they should be outsourcing the things that are not their core competency. Certainly they cannot outsource the entire hiring process–but they can outsource parts of it to a company like Interviewing.io.

Engineers come to Interviewing.io to practice their interview skills, where other engineers from top companies practice with them as an interviewer. When an engineer has practiced interviewing enough, they can use Interviewing.io to interview for real with real companies and find a job.

Aline Lerner is the CEO of Interviewing.io, and she knows about the software interviewing and recruiting process as much as anyone. After working as an engineer, she started studying recruiting, consulting with top companies to help them improve their process. From her observations, she created Interviewing.io. In this episode, we dissect the workflow that she created for engineers to improve at interviewing and find jobs, and also explore the insights that led her to starting Interviewing.io.

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You have heard the phrase: every company is becoming a software company. An insurance company is now supposed to turn into a software company that sells insurance. A clothing retailer needs to reinvent itself to be able to build software to manage the production and distribution of its clothing.

Software applications provide so much leverage to an organization, it seems smart to develop in-house software teams to build those applications. But does it really make sense? Is there a better alternative?

In the 90s outsourcing was a common solution to this problem. If you didn’t have software expertise at your company, you would hire a large consulting firm. These firms would often hire inexperienced offshore developers, and the resulting code quality was not so great.

Because of the bad experiences of the first Internet boom, companies became more cautious about outsourcing their engineering work–which led to today, where the standard is to hire your own software team.

The world has changed in ways that have made outsourcing a more viable solution.

Programming best practices are more widely understood. There is an international community of software engineers that share information on places like Stack Overflow, Quora, and Twitter.  Off-the-shelf collaboration tools make it much easier to communicate the requirements of a project to a team of developers.

Gigster is a company that is working to optimize the engineering of software projects. Large enterprises come to Gigster to build new projects from scratch–whether that project is a marketplace, a mobile application, or a machine learning model. Roger Dickey is the CEO of Gigster, and he joins the show to describe how Gigster works, and why it often makes sense for companies to focus on their core competency and outsource software engineering.

Some of our most popular episodes of Software Engineering Daily describe how leading software companies are being built–we have covered Giphy, Netflix, Digital Ocean, Stripe, and many others.  Download the Software Engineering Daily app for iOS or Android to hear all of our old episodes. They are easily organized by category, and as you listen, the SE Daily app gets smarter, and recommends you content based on the episodes you are hearing. If you don’t like this episode, you can easily find something more interesting by using the recommendation system.

The mobile apps are open sourced at github.com/softwareengineeringdaily. If you are looking for an open source project to hack on, we would love to get your help! We are building a new way to consume software engineering content. We have the Android app, the iOS app, a recommendation system, and a web frontend–and more projects are coming soon. If you have ideas for how software engineering media content should be consumed, or if you are interested in contributing code, check out github.com/softwareengineeringdaily, or join our Slack channel (there’s a link on our website)–or send me an email: [email protected]

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Advertising fraud continues to plague the Internet. We do not know the scope and scale of that fraud. How many ads on the Internet are viewed by bots? Estimations range from 2% to 99%.

Advertisers are slowly becoming more educated about fraud, thanks in part to Dr. Augustine Fou. Dr. Fou is a full-time advertising fraud researcher. He looks at data sets of billions of ad impressions to figure out how fraud works and help victims of ad fraud make their case.

Last year, Dr. Fou came on the show to give an overview of his perspective on the world of ad fraud. Today, we dive into the importance of Twitter in ad fraud schemes. We also talk about the severity of fraud on mobile apps. If you downloaded a flashlight app, or an alarm clock app, or a keyboard, that app could be displaying hidden ads that never actually show up.

Stay tuned at the end of the episode for Jeff Meyerson’s tip about getting into a new job: brought to you by Indeed Prime.

If you like this episode, we have done other shows about advertising fraud. Download the Software Engineering Daily app for iOS and Android to hear all of our old episodes, and easily discover new topics that might interest you. You can upvote the episodes you like and get recommendations based on your listening history. With 600 episodes, it is hard to find the episodes that appeal to you, and we hope the app helps with that. If you don’t like this episode, you can easily find something more interesting by looking at the recommendations in the app.

The mobile apps are open sourced at github.com/softwareengineeringdaily. If you are looking for an open source project to hack on, we would love to get your help! The Software Engineering Daily open source community is building a new way to consume software engineering content. We have the Android app, the iOS app, a recommendation system, and a web frontend. If you are interested in contributing, check out github.com/softwareengineeringdaily–or send me an email: [email protected]

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