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]

DMPs Go Way Beyond Segmentation

AboveAndBeyondAny AdExchanger reader probably knows more about data management technology than the average Joe, but many probably associate data management platforms (DMPs) with creating audience segments for programmatic media.

While segmentation, audience analytics, lookalike modeling and attribution are currently the primary use cases for DMP tech, there is so much more that can be done with access to all that user data in one place. These platforms sitting at the center of a marketer’s operational stack can make an impact far beyond paid media.

As data platforms mature, both publishers and marketers are starting to think beyond devices and browsers, and putting people in the center of what they do. Increasingly, this means focusing on giving the people what they want. In some cases that means no ads at all, while in others it’s the option to value certain audiences over others and serve them an ad first or deliver the right content – not just ads – based on their preferences.

Beyond personalization, there are DMP plays to be made in the areas of ad blocking and header bidding.

Ad Blocking

DMPs see a lot of browsers and devices on a monthly basis and strive to aggregate those disparate identities into a single user or universal consumer ID. They are also intimately involved in the serving of ads by either ingesting ad logs, deploying pixels or having a server-to-server connection with popular ad servers. This is great for influencing the serving of online ads across channels, but maybe it can help with one of the web’s most perplexing problems: the nonserving of ads.

With reports of consumers using applications to block as many as 10% of ads, wouldn’t it be great to know exactly who is blocking those ads? For publishers, that might mean identifying those users and suppressing them from targeting lists so they can help marketers get a better understanding of how much reach they have in certain audience segments. Once the “blockers” are segmented, publishers can get a fine-grained understanding of their composition, giving them insights about what audiences are more receptive to having ad-free or paid content experiences.

A lot of these issues are being solved today with specialized scripts that either aren’t very well coded, leading to page latency, or are scripted in-house, adding to complexity. Scripts trigger the typical “see ads or pay” notifications, which publishers have seen become more effective over time. The DMP, already installed and residing in the header across the enterprise, can provision this small feature alongside the larger application.

Header Bidding

Speaking of DMP architecture being in the header, I often wonder why publishers who have a DMP installed insist on deploying a different header-bidding solution to manage direct deals. Data management tech essentially operates by placing a control tag within the header of a publisher website, enabling a framework that gives direct and primary access to users entering the page. Through an integration with the ad server, the DMP can easily and quickly decide whether or not to deliver high-value “first looks” at inventory.

Today, the typical large publisher has a number of supply-side platforms (SSPs) set up to handle yield management, along with possibly several pieces of infrastructure to manage that critical programmatic direct sale. Publishers can reduce complexity and latency by simply using the pipes that have already been deployed for the very reason header bidding exists: understanding and managing the serving of premium ads to the right audiences.

Maybe publishers should be thinking about header bidding in a new way. Header-bidding tags are just another tag on the page. Those with tag management-enabled DMPs could have their existing architecture handle that – a salient point made recently by STAQ’s James Curran.

Curran also noted that the DMP has access, through ad log ingestion, to how much dough publishers get from every drop in the waterfall, including from private marketplace, programmatic direct header and the open exchanges. Many global publishers are looking at the DMP inside their stack as a hub that can see the pricing landscape at an audience level and power ad servers and SSPs with the type of intelligent decisioning that supercharges yield management.

Personalization

In ad technology, we talk a lot about the various partners enabling “paid, owned and earned” exposures to consumers, but we usually think of DMPs as essential only for the paid part.

But the composition of a web page, for example, is filled with dozens of little boxes, each capable of serving a display ad, video ad, social widget or content. Just as the DMP can influence the serving of ads into those little boxes, it can also influence the type of content that appears to each user. The big automaker might want to show a muscle car to that NASCAR Dad when he hits the page or a shiny new SUV to the Suburban Mom who shuttles the kids around all day.

Or, a marketer with a lot of its own content (“brands are publishers,” right?) may want to recommend its own articles or videos based on the browsing behavior of an anonymous user. The big global publisher may want to show a subscriber of one magazine a series of interesting articles from its other publications, possibly outperforming the CPA deals it has with third parties for subscription marketing.

This one-to-one personalization is possible because DMPs can capture not only the obvious cookie data but also the other 60% of user interactions and data, including mobile apps, mobile web, beacon data and even modeled propensity data from a marketer or publisher’s data warehouse.

Wouldn’t it be cool to serve an ad for a red car when the user has a statistically significant overlap with 10,000 others who have purchased red cars in the past year? That’s how to apply data science to drive real content personalization, rather than typical retargeting.

These are just some of the possibilities available when you start to think as the DMP as not just a central part of the ad technology “stack” but the brains behind everything that can be done with audiences. This critical infrastructure is where audience data gets ingested in real time, deployed to the right channels at speed and turned into insights about people. In a short period of time, the term “DMP” will likely be shorthand for the simple audience targeting use case inside of the data-driven marketing hub.

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

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