Experian has announced a new solution aimed to help marketers connect online and offline attributes and better understand their target audiences. The solution leverages machine-learning algorithms and probabilistic techniques to connect billions of identity signals and data elements, including Mobile Ad IDs (MAIDs) from a variety of internal and external sources.
Why we should care
Identity plays a crucial role in helping marketers understand who our customers are. The ever-changing technology landscape, however, creates challenges for marketers trying to analyze their customers’ activities. Experian’s solution will allow marketers to bridge gaps in identity resolution and bring together the appropriate data points to reach customers with relevant, timely campaigns.
“The combination of hundreds of digital and offline touchpoints, disjointed technology and data silos make it difficult for brands and agencies to gain a single customer view,” said Kevin Dean, Experian’s president and general manager of marketing services, North America. “Consumers need to be at the heart of every advertising campaign—and proper identity resolution is critical to accomplishing that objective. The ability to connect these data elements, with consideration to data privacy, opens the door for brands and agencies to create and deliver personalized messages that are timely and relevant to their audiences.”
More on the news
The new solution will be available via MarketingConnect, Experian’s identity resolution platform.
The MAID resolution capability was developed in collaboration with Experian Data Labs, Experian’s advanced analytics and development group.
It’s estimated that most Americans are exposed to around 4,000 to 10,000 ads each day. That’s a whole lot of opportunities to acquire new customers, and just as likely, annoy the everloving snot out of thousands of others. When you use remarketing to stay top-of-mind with customers, you’re walking a fine line between drawing in potential customers and infuriating your audience. Remarketing can and does work, but only if you can put customer experience above short-term vanity KPIs. Here’s how to do it and how to make the customer’s experience better using call tracking data.
Remarketing, retargeting, and why people hate it
What’s the difference between retargeting and remarketing? Remarketing is your overall strategy of reconnecting with customers and prospects after they have interacted with your brand. This could be a combination of email, paid digital media, direct mail and more. Retargeting refers to the cookie-based ads used to remarket to people after they have left your site on other sites as part of an ad network, such as Google Display Network ads.
Your typical non-marketer consumer may not know these terms or the inner workings of remarketing. They just know them as ads that seem to follow them everywhere they go after visiting your website, and they have some good reasons to hate them.
Ads are out of context
Have you ever been shopping for some kind of martech product and then get retargeting ads for it on your favorite hockey blog? If you’re a marketer, you probably just sigh and nod your head in shame that someone’s doing it wrong. Displaying ads out of context is one of the big reasons why consumers feel like they’re being “followed” by you. It sticks out like a sore thumb because it’s just the wrong place and the wrong time. However, if you can contextualize your remarketing, the ads will seem natural and do what they’re supposed to do — keep your brand top-of-mind. When you see ads for the hockey gear you’ve been shopping for on the hockey blog and email automation on marketing industry websites, you nod your head in approval and think “YEAH, these folks know what they’re doing!” Then you buy that 12-pack of pucks and call back that martech SDR who has been hounding you for the last six weeks. Mission accomplished!
Your ads are absofreakinlutely everywhere, forever
The more times someone sees your ad, the more likely they’ll remember you, right? That might be the case, but they’ll probably be remembering that they’d like to strangle you. A study performed by Skin Media and RAPP Media aimed to find out how this repetitiveness affects consumers. In the study, they found that people think that seeing a retargeted ad five or more times is “annoying,” while seeing it ten or more times makes them “angry”. Not the experience you’re looking for. More than half of the visitors polled said that they may be interested in the ad the first time they see it, even though only 10% report making a purchase as a result of seeing a remarketed ad. Think carefully when you are setting your frequency caps and make sure you are not inundating (and annoying the hell out of) your customers with ads.
Getting retargeted for stuff you already bought
Step 1: Buy a new power drill. Step 2: See millions of retargeting ads for the same darned drill. Step 3: Scream at your computer “GAWD, fix your suppression, dummies!” The average consumer may also find this rather inept, but more likely, they’re going to be turned off by it. Proper post-conversion ad suppression makes your marketing much more efficient and saves your customers from the agony of being reminded of their purchase for six weeks, or worse, seeing an ad with a lower price than they paid and making them feel conned.
How call tracking data can make the remarketing experience better
Particularly in the post-cookies age we live in, where the use of third-party cookies for remarketing is being smashed by new regulations and browser-level cookie-blocking, using every source of first-party data you have at hand for remarketing is critical. If your business gets a lot of sales inquiries from inbound phone calls, your remarketing picture gets even muddier. A potential customer may have navigated to your website and clicked on a page or product before calling you and either asking a question or ultimately making a purchase. Either way, you are left with a data gap that leaves you open for making bad remarketing decisions that will annoy your customers and waste your marketing budget.
You can bridge this data gap and get your hands on precise first-party data for remarketing by using a call tracking and conversational analytics platform. When your customers call you, they are literally telling you what they want and how they talk about it. To feasibly classify customer conversations into useful digital datasets, you need an automated system that can understand what’s being said and accurately derive meaning from it. Your call tracking platform should be able to accomplish a few things:
Automatically determine the outcome of inbound phone calls
Predict and classify call type (e.g. sales call, service call, etc.)
Collect digital journey data such as UTM, keywords, and GCLID
Push marketing intelligence collected from calls to your martech stack in real time
With this type of functionality, you can fine-tune your remarketing campaigns without doing a lot of heavy lifting. The data can be fed to your DMP and/or ad network to automate the process in real time. And when you understand the nature of a call, you can optimize your media for higher ROI, which can be particularly helpful when you are nailing down the next best step in your marketing, whether that be retargeting ads for someone who did not make a purchase, or suppressing ads for someone who did. You can also use call data to feed to Google’s automated bidding algorithm to adjust your bids according to what is (or isn’t) happening on the phone.
Conversational analytics tools like Invoca’s new Signal Discovery take this to a new level of precision and granularity, as they can help you find out things about phone conversations that you don’t even know to look for. Over 56% of marketers have no idea what’s said during the calls that they drive or what the outcomes of those calls are. It’s a big data gap that marketers shouldn’t have to live with. “Conversations are overflowing with insights that don’t always see the light of day outside the contact center. As a result, many companies are missing out on opportunities to create a more consistent and positive customer experience across human and digital touchpoints,” said Dan Miller, lead analyst and founder at Opus Research.
Signal Discovery solves this issue by enabling marketers to quickly gain new insights from tens of thousands of conversations and take action on them in real time. From there, you’re able to drill down into each topic to understand caller behavior and then create a “signal” that Invoca will listen for in future calls so you can see exactly when a specific topic is discussed and can automate your marketing based on this data. No more guesswork, no more risky call assumptions.
With all this data, you can make your remarketing efforts more targeted, relevant, efficient, and above all, less annoying.
Mastercard has purchased customer data and loyalty platform SessionM. Terms weren’t disclosed but the startup raised almost $100 million over four rounds.
SessionM is behind loyalty programs for a wide range of companies including Coke, L’Oreal and Chipotle. It uses customer data and numerous behavioral and intent signals to deliver personalized (primarily) mobile offers.
Loyalty 2.0. Mastercard said in its press materials, that “The addition of SessionM will enhance Mastercard’s ability to help brands around the world deliver personalized, real-time offers and comprehensive campaign measurement based on robust, data-driven insights . . . SessionM helps brands create and manage consumer engagement and loyalty programs with industry-leading technology that powers a complete loyalty solution — from data management to campaign execution to program measurement.”
Moving beyond the marketing jargon, why did Mastercard buy SessionM? The deal actually makes perfect sense, as Mastercard seeks to gain an edge against payment card rivals and offer value-added services to its B2B customers.
The acquisition’s rationale. It’s about bringing a lot more data, targeting sophistication and measurement to branded credit card loyalty programs. A SessionM blog post reveals the rationale behind the acquisition:
74% of Americans possess a store credit card; Cardholders receive rewards, discounts and exclusive experiences, while merchants receive a free ad in the customer’s wallet, an additional stream of revenue through credit card fees, and in theory, more ‘sticky’ customers . . . Just having a card to use will increase store sales by some 28% to 30%.
Brands can enhance their retention strategy by combining branded credit card + loyalty program [and] gain the ability to recognize, reward and improve communications with cardholders, improve customer experience for non-card members, and acquire more cardholders with personalized interactions.
Brands that combine a branded label credit cards with a loyalty/rewards program achieve greater results because a single program better reflects the simplicity that customers want and eliminates pain points, such as redemption limitations.
Why we should care. Mastercard has been working with digital marketing platforms for some time, using its transaction and POS data to enable targeting and attribution by third parties, including Google. Now the company will be able to offer a powerful data-driven loyalty program along with branded credit cards to its B2B customers.
That program will not only provide customer insights for personalized offers and targeting to retailers and brands, it will enable closed-loop measurement at the point of sale. SessionM will also drive additional revenue for Mastercard. It’s a pretty compelling proposition all the way around.