Big vendor risks: Friday’s daily brief
Plus, a deep learning solution from Qubit.
Good morning, Marketers, and what do marketing ops professionals do when they get together? Well, one thing they do is conduct a MoSCoW evaluation. That’s a prioritization technique based on deciding what you Must Have, Should Have, Could Have plus Wow. I’ll come back to Wow. The group, convened in an Atlanta hotel for a couple of days by MO Pros community organize Mike Rizzo, applied MoSCoW to the task of compiling one central repository of information about the services offered by a marketing ops team — aimed at their internal clients, but also documenting processes for the team’s own benefit (the group decided to apply different permissions to different roles to avoid the sales team knowing more than they need to know). The assessment was led by M.H. Lines, CEO of Stack Moxie. Must-haves included information on lead scoring and lead management and a data dictionary. The Wow factor is something that might not be essential but makes for a delightful user experience. In this case, the group decided to Wow by adding an AI-driven chatbot. My only contribution was to suggest not having several different versions on the repository created by different people for different reasons. Kim Davis Editorial Director
Real Story on MarTech: Big vendor stability?
Real Story Group’s founder, Tony Byrne, tends to think the vast majority of the reported 8,000 martech vendors will survive, but fears will persist about individual vendors’ viability. Many smaller businesses do fail. Software vendors are no different, and who wants to get stuck with an unsupported product? Byrne has come to the conclusion that the very biggest vendors can actually carry the highest risks in terms of continuity. Big martech suite vendors aren’t going to fail as companies, but they will kill or replace individual products at the drop of the hat. They are constantly buying other vendors and calving off pieces of their portfolios. Meanwhile, their own product strategies can shift quickly, due to staff turnover, equity market shifts or simple faddishness, to which all martech players are equally susceptible. Consider some examples:
- Google is infamous for killing platforms;
- Microsoft has gone through several incompatible renditions of marketing automation services around its Dynamics suite, and late last decade deprecated SharePoint as a public-facing WCM — giving up on its third attempt in this space;
- Not to be outdone, the latest Salesforce WCM offering is that vendor’s third attempt at this market (licensees of the first two attempts could not be reached for comment…);
- Salesforce also inconveniently licenses two CDPs today — likely an unsustainable situation for licensees of the ultimate loser;
- Adobe has had fewer démarches, likely because it’s been more circumspect in M&A, though fans of Macromedia digital tools may still hold some bitter memories; and
- Oracle has bought, sold, and developed such a wide array of overlapping digital and marketing platforms that a family tree would likely take up your entire screen — some acquired platforms endure, many have died of neglect.
Qubit leverages deep learning for its new CommerceAI solution
Qubit, the personalization engine for e-commerce, has launched Qubit CommerceAI, a new offering that supports 1:1 personalization in the moment. The tool uses deep learning rather than standard machine learning — a technique that employs non-linear layering of algorithms to discover pattern recognition across large data sets. It brings together customer data and product data, sifting through possibly thousands of SKUs, to make real-time 1:1 product recommendations, and to recommend the next best products that are shown. It also recommends personalized content and triggers automated responses for abandonment recovery. Why we care. Ecommerce exploded in 2020, with an estimated leap of 44% YoY in online spending. Of course, that’s good news for merchants with robust e-commerce offerings, but it also means the space is more competitive than ever. Advanced AI offers the promise of keeping up with the personal needs of thousands of customers. Qubit is looking to push the envelope by deploying the “neural networks” of deep learning, instantly to recognize and respond to customer behavior.
“The whole value proposition for Google is that it discriminates between different possible results”
While there is some merit to the motives behind regulating Google, the idea that it should be classified and treated as a public utility or common carrier simply doesn’t apply — that’s the takeaway from Gilad Edelman’s article for Wired. “Public utility comes from a contractual relationship between the government and that entity that is supposed to be the public utility,” said Barbara Cherry, a professor at the Indiana University Media School who studies common carriage and public utility law. There is no such relationship between Google and governing bodies. “A common carrier was someone who offered to carry something to any member of the public,” wrote Edelman, “Anyone who chose to do business that way was subject to certain legal duties, including nondiscrimination.” The thing is, Google doesn’t promise to behave neutrally because the foundations of its business are ranking search results and auctioning off ad inventory — two fundamentally discriminatory practices. But surely, no one wants Google to stop auctioning off ad space or ranking results. “If you mean nondiscriminatory in a much narrower sense, like does Google’s algorithm include whether the webpage has a conservative or a liberal tint, or is based on anything else—gender, race, what have you—then, yeah, Google might say that they’re nondiscriminatory in these narrower senses. But this doesn’t easily map into the question of common carriage,” said Scott Jordan, former chief technologist at the Federal Communications Commission and a current professor of electrical engineering and computer science at UC Irvine. The varying levels of familiarity with technology and law across stakeholders (the regulators, big tech and the general public) adds another layer of complexity that tends to stall momentum — and for good reason, since rushing these initiatives could establish poor precedence for the future.
Quote of the day
“I had a call with a huge global brand today who is actively looking to decrease their spend on ads and to instead go direct-to-creators, allowing them to unleash their own forms of creativity and to earn equity. These new models are coming, fast.” Zoe Scaman, founder Bodacious The post Big vendor risks: Friday’s daily brief appeared first on MarTech. MarTech
About The Author
Kim Davis is the Editorial Director of MarTech. Born in London, but a New Yorker for over two decades, Kim started covering enterprise software ten years ago. His experience encompasses SaaS for the enterprise, digital- ad data-driven urban planning, and applications of SaaS, digital technology, and data in the marketing space. He first wrote about marketing technology as editor of Haymarket’s The Hub, a dedicated marketing tech website, which subsequently became a channel on the established direct marketing brand DMN. Kim joined DMN proper in 2016, as a senior editor, becoming Executive Editor, then Editor-in-Chief a position he held until January 2020. Prior to working in tech journalism, Kim was Associate Editor at a New York Times hyper-local news site, The Local: East Village, and has previously worked as an editor of an academic publication, and as a music journalist. He has written hundreds of New York restaurant reviews for a personal blog, and has been an occasional guest contributor to Eater.
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