How AI will Change UX

user_experience_sarah_weise In 1960, the US Navy coined a design principle: Keep it simple, stupid.

When it comes to advertising and marketing technology, we haven’t enjoyed a lot of “simple” over the last dozen years or so. In an increasingly data-driven world where delivering a relevant customer experience makes all the difference, we have embraced complexity over simplicity, dealing in acronyms, algorithms and now machine learning and artificial intelligence (AI).

When the numbers are reconciled and the demand side pays the supply side, what we have been mostly doing is pushing a lot of data into digital advertising channels and munching around the edges of performance, trying to optimize sub-1% click-through rates.

That minimal uptick in performance has come at the price of some astounding complexity: ad exchanges, third-party data, second-price auctions and even the befuddling technology known as header bidding. Smart, technical people struggle with these concepts, but we have embraced them as the secret handshake in a club that pays it dues by promising to manage that complexity away.

Marketers, however, are not stupid. They have steadily been taking ownership of their first-party data and starting to build marketing tech stacks that attempt to add transparency and efficiency to their outbound marketing, while eliminating many of the opaque ad tech taxes levied by confusing and ever-growing layers of licensed technology. Data management platforms, at the heart of this effort to take back control, have seen increased penetration among large marketers – and this trend will not stop.

This is a great thing, but we should remember that we are in the third inning of a game that will certainly go into extra innings. I remember what it was like to save a document in WordPerfect, send an email using Lotus Notes and program my VCR. Before point-and-click interfaces, such tasks were needlessly complex. Ever try to program the hotel’s alarm clock just in case your iPhone battery runs out? In a world of delightful user experience and clean, simple graphical interfaces, such a task becomes complex to the point of failure.

Why Have We Designed Such Complexity Into Marketing Technology?

We are, in effect, giving users who want big buttons and levers the equivalent graphical user interface of an Airbus A380: tons of granular and specific controls that may take a minute to learn, but a lifetime to master.

How can we change this? The good news is that change has already arrived, in the form of machine learning and artificial intelligence. When you go on Amazon or Netflix, do you have to program any of your preferences before getting really amazing product and movie recommendations? Of course not. Such algorithmic work happens on the back end where historical purchases and search data are mapped against each other, yielding seemingly magical recommendations.

Yet, when airline marketers go into their ad tech platform, we somehow expect them to inform the system of myriad attributes which comprise someone with “vacation travel intent” and find those potential customers across multiple channels. Companies like Expedia tell us just what to pay for a hotel room with minimal input, but we expect marketers to have internal data science teams to build propensity models so that user scores can be matched to a real-time bidding strategy.

One of the biggest trends we will see over the next several years is what could be thought of as the democratization of data science. As data-driven marketing becomes the norm, the winners and losers will be sorted out by their ability to build robust first-party data assets and leverage data science to sift the proverbial wheat from the chaff.

This capability will go hand-in-hand with an ability to map all kinds of distinct signals – mobile phones, tablets, browsers, connected devices and beacons – to an actual person. This is important for marketers because browsers and devices never buy anything, but customers do. Leading-edge companies will depend on data science to learn more about increasingly hard-to-find customers, understand their habits, gain unique insights about what prompts them to buy and leverage those insights to find them in the very moment they are going to buy.

In today’s world, that starts with data management and ends with finding people on connected devices. The problem is that executing is quite difficult to automate and scale. Systems still require experts that understand data strategy, specific use cases and the value of an organization’s siloed data when stitched together. Plus, you need great internal resources and a smart agency capable of execution once that strategy is actually in place.

However, the basic data problems we face today are not actually that complicated. Thomas Bayes worked them out more than 300 years ago with a series of probabilistic equations we still depend on today. The real trick involves packaging that Bayesian magic in such a way that the everyday marketer can go into a system containing “Hawaiian vacation travel intenders” for a winter travel campaign and push a button that says, “Find me more of these – now!”

Today’s problem is that we depend on either a small amount of “power users” – or the companies themselves – to put all of this amazing technology to work, rather than simply serving up the answers and offering a big red button to push.

A Simpler Future For Marketers?

Instead of building high-propensity segments and waiting for users to target them, tomorrow’s platforms will offer preselected lists of segments to target. Instead of having an agency’s media guru perform a marketing-mix model to determine channel mix, mar tech stacks will simply automatically allocate expenditures across channels based on the people data available. Instead of setting complex bid parameters by segment, artificial intelligence layers will automatically control pricing based on bid density, frequency of exposure and propensity to buy – while automatically suppressing users who have converted from receiving that damn shoe ad again.

This is all happening today, and it is happening right on time. In a world with only tens of thousands of data scientists and enough jobs for millions of them, history will be written by the companies clever enough to hide the math on the server side and give users the elegance of a simple interface where higher-level business decisions will be made.

We are entering into a unique epoch in our industry, one in which the math still rules, but the ability of designers to make it accessible to the English majors who run media will rule supreme.

It’s a great time to be a data-driven marketer! Happy New Year.

Follow Chris O’Hara (@chrisohara) and AdExchanger (@adexchanger) on Twitter. 

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CX: The CFO’s Best Friend!

BFFS

When CFO’s embrace data and use it to drive customer experience, good times ensue.

 

Although it’s starting to become a well-worn aphorism, “data is the new oil” resonates more than ever. Like oil, data is an abundant resource, but it doesn’t become useful until it is refined for use and turned into fuel.

Without the proper refinement, big data may be worthless. The stock of big data unicorn Palantir, for example, sunk on news that it lost key client relationships due to a lack of perceived value. The company collected abundant data from CPG companies but was unable to apply it to practical use cases, according to a recent article.

Marketers are starting to turn away from using abundant, yet commoditized, third-party data sources in exchanges and move toward creating peer-to-peer data relationships and leveraging second-party data for targeting. This speaks to the refinement of targeting data: Better quality in the raw materials always yields more potent fuel for performance. Not all data is the same, and not every technology platform can spin data straw into gold.

Marketers have been using available data for addressable marketing for years, but now are starting to mine their own data and get value from the information they collect from registrations, mobile applications, media performance and site visitation. Data management platforms (DMPs) are helping them collect, refine, normalize and associate their disparate first-party data with actual people for targeting.

This is a beautiful thing. Technology is enabling marketers to mine their own data and own it. Yet many marketers are still just scraping the surface of what they can do, and using data primarily for the targeting of addressable media.

Some, however, are starting to deliver customer experiences that go beyond targeting display advertising by using data to shape the way consumers interact with their brands beyond media.

The case for personalization – customer experience management, or CX – is palpable. When the Watermark Group studied [PDF] the cumulative stock performance of Forrester Research-rated “leaders” or “laggards” in customer experience, the results were staggering. During a period in which the S&P 500 grew by 72%, those focused on personalized experiences outperformed the market by 35%, and the laggards underperformed by 45% on average. That’s a delta of nearly 80% in stock price performance between the winners and losers.

Moreover, 89% of customers who have a, unsatisfactory experience will leave a brand, according to a recent study; the cost of reacquiring a churned customer can run up to seven times the amount it took to win a new customer.

The stakes could not be higher for marketers and publishers looking to drive bottom-line performance. For many companies, whether they are marketing print or online subscriptions, promoting their content or selling products off the shelf, it’s hard to justify the heavy costs associated with licensing platforms to gather the right data and use that data to drive relevant customer experiences to their CFOs. Yet, when looking at big company priorities on multiple surveys, the desire to “create more relevant customer experiences” is right up there with “earn more revenue” and “increase profits.” Why?

The simple answer is that customer experience has an enormous impact on both revenue and profitability. Giving new customers the right experience provides a higher probability of winning them, and giving existing customers relevant experiences reduces churn – and creates opportunities to sell them more products, more often. When both top-line revenue and profitability can be driven through a single initiative, most CFOs start to invest and will continue to invest as results confirm the initial thesis.

Take the “heavy user” of a quick-service restaurant who dines several times a week and consistently transacts an over-average per-visit receipt. QSRs understand the impact these valued customers have on the bottom line. These users provide a strong baseline of predicable revenue, are usually the first to try new product offerings and respond to market-facing initiatives, such as discounting and couponing, which can strategically increase short-term receipts. Smart marketers should not be content to sit back and let this valuable segment remain stagnant or find new offerings with a competitive restaurant. They must show these users that they are valued, ensure they retain or increase store visits and keep them away from the hamburger next door.

That can be as simple as offering a coupon for a regular’s favorite order. Or it can be as complex as developing a mobile application that enables the customer to order his food in advance and pick it as soon as it’s ready.

Since the restaurant collects point-of-sale data and has authenticated user registration data from the mobile app, it can now personalize the customer’s order screen with his most popular orders to shorten the mobile ordering experience. Perhaps the app can offer special discounts to frequent diners for trying – and rating – new menu items. When on the road, the app can recommend other locations and direct him right to the drive-in window through popular map APIs. The possibilities are endless when you start to imagine how data can drive your next customer interaction.

Marketers and publishers are quickly embracing their first-party data and aligning it with powerful applications that drive customer experience, increase profits, reduce customer churn and boost lifetime value.

It’s a great time to be a data-driven marketer.

[This post originally appeared in AdExchanger on 5/23/16]