Going all-in on AI (soon): Friday’s daily brief
Plus Helen Abramova on the explosion of MOPs-related content
MarTech’s daily brief features daily insights, news, tips, and essential bits of wisdom for today’s digital marketing leader. If you would like to read this before the rest of the internet does, sign up here to get it delivered to your inbox daily.
Good morning, Marketers, it’s been an exciting week at MarTech.
Change has been a constant theme, and Kim Davis tackles the global food supply chain with his feature on AGI’s pandemic responses. When one channel cuts out (in AGI’s case, live events), this puts greater emphasis on other areas of your content footprint. Many customers are still trying to engage, and will find you where they can.
With more attention, companies face greater pressure to respond. And that’s where transformation really comes in. If your customer is transformed and expects quicker digital response times, they expect a trusted brand to change with them. This could mean adopting AI technologies, or advancing the way you speak to your customers.
Also, look below at our takeaways from Google’s I/O developers conference and how companies plan to adopt AI technology. And if you have feedback about MarTech, let me know at [email protected]
Portrait of a pivot
What changed for AGI under COVID? “I think everything changed, to be quite honest,” said David Postill, AGI’s SVP Marketing and Customer Experience. “Historically, we had a lot of salespeople on the ground. On the B2B side of things, we would rely on events, trade shows. As everybody got stuck at home, we really had to reinvent everything.” AGI creates the equipment, facilities, processes and technologies which support the global food infrastructure. Its business is built across five platforms — seed, fertilizer, grain, feed and food — and 35 brands, and it operates in 102 countries.
There was a complete pause on trade shows – “We would do hundreds around the world and that went to zero overnight,” Postill said. “We pivoted to a content play. We launched something called AGI Live — we came up with it in about 30 days. It turned into a series of webinars.” AGI also had to change its approach to equipment training, which used to happen in person, in seminars, or even by going to farms to calibrate equipment. “We adopted a learning management system and went entirely digital with it.”
The AGI website became even more important as an engagement channel. “When I arrived, we had about 42 independent websites, and nearly 80% of them were not even mobile-optimized. It was a soup of online presence. We had to have a home base for our universe of content. We needed to sunset all of those brand websites, migrate them into a single platform, and then build it so that it’s scalable around the world.”
This all required a CMS platform. Episerver, since rebranded as Optimizely, came on board about three years ago, and AGI heavily leverages its automated content and product recommendation capabilities. “We just can’t go fast enough in that area,” said Postill. “That unique product mix for that unique customer; as much as we can personalize that experience, that’s top of the list for us.”
LaMDA LaMDA LaMDA
Google’s I/O developer conference, held virtually this year of course, just wrapped. Here are our selected highlights from the product announcements.
LaMDA’s open-ended voice conversations. Sundar Pichai, CEO of Google’s parent company Alphabet, previewed a new conversational model called LaMDA, or “Language Model for Dialogue Applications,” at the event on Tuesday. The new language model is designed to carry on an open-ended conversation with a human user without repeating information. LaMDA is still in early-phase research, with no rollout dates announced. LaMDA was trained on dialogue, and Google has put an emphasis on training it to produce sensible and specific responses, instead of more generic replies like “that’s nice,” or “I don’t know.”
MUM the multi-tasker. Google SVP Prabhakar Raghavan showcased a new technology called Multitask Unified Model (MUM). Similar to BERT, it’s built on a transformer architecture but is far more powerful (1,000 times more powerful) and is capable of multitasking to connect information for users in new ways. The company is currently running internal pilot programs with MUM, although no public rollout date was announced.
On stage at I/O, Raghavan provided some examples of the tasks that MUM can handle at the same time:
- Acquire deep knowledge of the world;
- Understand and generate language;
- Train across 75 languages; and
- Understand multiple modalities (enabling it to understand multiple forms of information, like images, text and video).
ShoppingGraph and a partnership with Shopify. Bill Ready, the company’s president of commerce and payments, revealed details about its Shopping Graph, the real-time dataset that connects shoppers with billions of product listings from merchants all across the internet.
“Building on the Knowledge Graph, the Shopping Graph brings together information from websites, prices, reviews, videos and, most importantly, the product data we receive from brands and retailers directly,” Ready said. The AI-enhanced model works in real-time and is designed to show users relevant listings as they shop across Google.
Google has also partnered with Shopify to enable the platform’s 1.7 million merchants to show their products across Google Search, Shopping, Image search and YouTube.
Going all-in on AI, this year or next
Businesses are looking to adopt AI solutions. If they aren’t implementing some of these technologies in 2021, they say they’re totally doing it next year. Those are the somewhat ambivalent results included in a Deloitte study discussed yesterday by Tom Davenport in a virtual talk hosted by Travelers. Davenport is a Senior Advisor at Deloitte, professor at Babson College and author of The AI Advantage (MIT Press).
Between one half and two-thirds of the companies surveyed have technologies like statistical machine learning (67%), natural language processing (58%) and deep-learning neural networks (54%) currently in place, Davenport said. When 2022 is included in the question of if they’ll have it, the percentage spikes to 94-97%. So there’s a lot of companies who haven’t made the leap that expect to in the next year, or are saying they do.
The keys to adoption that Davenport shared apply both to marketing teams and the organization as a whole. Marketing-related objectives for the use of AI shared by these businesses included enhancing relationships with customers/clients (22%), improving decision making (21%) and discovering new insights (17%).
Davenport recommends these principles when transforming your organization and adopting AI:
- Think big about how AI can transform strategy, business model or how work gets done (processes);
- Start small with pilot projects and less-ambitious goals, then scale or combine them;
- Upskill employees and offer job options and time to transition to them;
- Reprioritize projects, but don’t ease up on current ones;
- Put an ethical framework in place; and
- Create AI leadership and governance.
Why we care. Digital transformation and AI implementation remain people-first initiatives, especially when dealing with creative people on marketing teams and the customers they engage. If there is a lag at some organizations, it’s because organizational movement toward transformation depends on people, attitudes and goals company-wide. The pandemic and resulting financial downturn filled companies with a lot of fear, understandably, in 2020 and 2021. We’ll have to watch closely to see if more orgs are inspired to embrace AI technology.
Quote of the day
“New channels, communities, events…MOPs related content is just blowing up. Employers are hiring frantically, people get promoted, switch jobs, open consultancies. Suddenly, so many amazing professionals do MOPs. Obviously, many of them were doing it all [along], but only recently made a professional ‘coming out.’” Helen Abramova, Marketing Operations Lead, Verizon