Q&A with Jaime Punishill, CMO at Lionbridge

Jaime Punishill, CMO at Lionbridge is an innovative marketing, channel, and product executive with a proven track record for finding blue ocean strategies and delivering scalable business operations.

Jaime is also an expert in operationalizing design thinking, translating new concepts and trends into workable business plans and operations, and delivering pragmatic innovation within a large enterprise.

MEDIA 7: Could you tell us about your role and journey into marketing?
JAIME PUNISHILL:
As Chief Marketing Officer for Lionbridge, I oversee brand, demand gen, corporate communications, marketing, and customer research. Interestingly enough, I’m not a classic marketer by training. I have spent most of my career on the product side and in digital transformation. I’ve been doing that since the mid-1990s. At some point, it became clear that marketing was the next area that universal digital transformation was going to overtake, and areas like user experience and many other digital functions that had been done separately were going to move under the remit of marketing. I slowly moved into the marketing universe and helped with big digital transformation in my previous company. That led me to take on all our brand, advertising, and integrated marketing. In that way, I ended up with a more traditional marketing role, and that led me to Lionbridge.

M7: As a CMO, what are the biggest challenges you face?
JP:
One of the biggest challenges is the unbelievable explosion in the martech space. I get over 300-400 emails and dozens of phone calls every day from different vendors who are trying to push different tools to help optimize the new digital experience. Keeping track of the rapid pace of evolution and trying to integrate all those tools is single-handedly probably one of the biggest challenges for CMOs. It swallows historical challenges, like getting the company to buy into a new understanding of the digital universe, or getting people to appreciate customer research and customer feedback.
These are always challenges, but they are all lower in scale now than just sheer digital transformation and the volume of tools and resources that accompany that transformation. There’s so much noise, and it’s really hard to tell what’s real and what’s not real.


"Keeping track of the rapid pace of evolution and trying to integrate all those tools is single-handedly probably one of the biggest challenges for CMOs."

M7: What was the most successful marketing campaign you have ever worked on? What made it so successful?
JP:
In my previous organization, we led a re-brand of the company in its first-ever national advertising campaign. That meant we weren’t constrained by existing rules and assumptions about how things had to be done, so we were able to quite creatively and innovatively harness several digital channels in a way that many of our competitors hadn’t. In terms of revenue or asset flows, new customers, traffic to the website and just about every other metric, it was a tremendous lift. That’s probably the single-most effective marketing campaign I’ve worked on, and it was completely comprehensive. It had a brand component, a communications component, a community component. It had very specific direct targeting and campaigns along with a goal of raising basic awareness. We were targeting by social media profile and audience. I think it was successful largely because it was multi-faceted and end-to-end.

M7: At Lionbridge, how do you see AI evolving with digital media?
JP:
For AI, we are still really in a hype-cycle. There is absolutely no doubt that AI and everything that falls under its purview will have a profound impact on the scale, data, and decisions we are able to process as marketers. The number of simulations and tests we will be able to run to optimize a campaign or project pre-launch, plus the ability for us to pivot real-time and use new insights, will be absolutely profound. But I think we are still very early in the journey. There’s more hype than substance right now. I’m not skeptical about AI’s eventual impact at all. But right now, the tools are not mature, and we are not mature in our understanding of AI, even regarding some of the most impactful ways to use it. So, I’m super optimistic over a 3-5-7-year period. But, I’m very skeptical over a 6-12-24-months period.


"AI and everything that falls under its purview will have a profound impact on the scale, data, and decisions we are able to process as marketers."

M7: How does the acquisition of Gengo strengthen Lionbridge’s position in machine learning?
JP: We are one of the world leaders in AI training data services. The fuel that makes AI work effectively is incredibly high volumes of high-quality data. And the problem is, as we know, most organizations have not done a good job being stewards of their data. Their data exists in lots of places, their data is not clean, it’s not annotated or mapped, there’s no organizing taxonomy around its structure. CDPs are still relatively early for a lot of folks, and so the catch is that you have lots of data, but that data may be largely unusable. Sort of like, there is a lot of oil in the ground, but just because the oil is in the ground doesn’t mean you have gas that works in your car or in a plane. A lot has to happen to refine it, to get it ready. The same is true with data “fuel.”

The good news is that we are one of the world leaders in helping companies refine their data so it’s usable in training their AI systems. Identifying and collecting data, and giving that data meaning, for example, is it metadata or actual data, is that an important variable or not an important variable, etc., is an integral step in the machine learning process. We help companies collect data, organize it, give it meaning so it can best feed our customers’ AI platforms.

We do this by activating our one million-strong SmartCrowd. The Gengo platform really helps us create a scalable system that will allow more companies to be able to improve the quality of their AI training data and, in turn, the quality of their AI.

M7: How do you stay updated on the latest trends in marketing technology?
JP: 
I read a lot. I get a couple of hundred emails a day. Part of that is because I sign up for lots of different sources of information. I think you have to consume a tremendous amount of information right now to pull in all the weak signals. And I probably dedicate more of my days than I would normally to looking at new capabilities just to keep me informed and up-to-date. This allows me to get a sense of when I think something is at a point where we can use it and harness something early for a strategic advantage.


"Most organizations have not done a good job being stewards of their data. Their data exists in lots of places, their data is not clean, it’s not annotated or mapped, there’s no organizing taxonomy around its structure."

M7: What are the top 3 trends that you foresee for 2019 going into 2020?
JP:
We are going to hear more about AI. We will see more examples of it not working in the next 18 months than we will see examples of it working, but I think that’s a short-term phenomenon, and we will work out the issues.

I think there is absolutely no doubt that we are going to see an increase in the production and consumption of video and its import in the production cycle. People are consuming more and more videos, and even B2B buyers are much more heavily consuming videos as a way to absorb a lot of information in a pretty short period of time. In 2-3 minutes, you can convey a lot more, and frankly people can understand a lot more than if they spend 20 minutes reading a whitepaper or something of that nature.

And clearly, voice search is on a big rise. There are a couple of key reasons for that. If you think about the US workforce, half of it now only knows a universe where Google is the dominant information organizational paradigm. Pair that with the sheer explosion of speech applications and devices, whether in your home, in your car, or in your hand—today, every phone is speech-enabled. It’s clear that all the large players are investing a tremendous amount of effort into proving the quality of voice search, and an increasing number of users are speaking to a device or multiple devices to get information. That’s a real challenge for organizations and marketers, because the way people speak to their device and physically ask for information is not the same as how they type a query into a search engine. So, the whole way in which we optimize and organize for search results in a voice-search world is quite different than in a text-based or type-based universe.  

M7: What is your superpower?
JP:
I’m not really sure I have a superpower. But there’s something I think I do that seems to be more of a struggle for some others. I’m able to assemble a collection of weak signals to predict what is going to happen before it happens. I really believe all the information is there, but I seem to be able to use that information to make some good bets about what the future holds.

ABOUT LIONBRIDGE

Lionbridge partners with brands to break barriers and build bridges all over the world. For more than 20 years, we have helped companies connect with global customers by delivering marketing, testing and globalization services in more than 300 languages. Through our world-class platform, we orchestrate a network of 500,000 passionate experts in 5,000-plus cities, who partner with brands to create culturally rich experiences. Relentless in our love for linguistics, we use the best of human and machine intelligence to forge understanding that resonates with our customers’ customers. Based in Waltham, Mass., Lionbridge maintains solution centers in 27 countries. Learn more at www.lionbridge.com.

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Now generally available, and ready for both analytical and transactional processing for apps originally built on MongoDB. Announced in public preview in early 2023, SingleStore Kai is an API to deliver over 100x faster analytics on MongoDB® with no query changes or data transformations required. Today, SingleStore Kai supports BSON data format natively, has improved transactional performance, increased performance for arrays and offers industry-leading compatibility with MongoDB query language. Projections: To further advance as the world’s fastest HTAP database, SingleStore has added Projections. Projections allow developers to greatly speed up range filters and group by operations by introducing secondary sort and shard keys. Query performance improvements range from 2-3x or more, depending on the size of the table. With this latest release, SingleStore becomes the industry’s first and only real-time data platform designed for all applications, analytics and AI. SingleStore supports high-throughput ingest performance, ACID transactions and low-latency analytics; and structured, semi-structured (JSON, BSON, text) and unstructured data (vector embeddings of audio, video, images, PDFs, etc.). Finally, SingleStore’s data platform is designed not just with developers in mind, but also ML engineers, data engineers and data scientists. “Our new features and capabilities advance SingleStore’s mission of offering a real-time data platform for the next wave of gen AI and data applications,” said Nadeem Asghar, SVP, Product Management + Strategy at SingleStore. “New features, including vector search, Projections, Apache Iceberg, Scheduled Notebooks, autoscaling, GPU compute services, SingleStore Kai™, and the Free Shared Tier allow startups — as well as global enterprises — to quickly build and scale enterprise-grade real-time AI applications. We make data integration with third-party databases easy with both CDC in and CDC out support.” "Although generative AI, LLM, and vector search capabilities are early stage, they promise to deliver a richer data experience with translytical architecture," states the 2023 report, “Translytical Architecture 2.0 Evolves To Support Distributed, Multimodel, And AI Capabilities,” authored by Noel Yuhanna, Vice President and Principal Analyst at Forrester Research. "Generative AI and LLM can help democratize data through natural language query (NLQ), offering a ChatGPT-like interface. Also, vector storage and index can be leveraged to perform similarity searches to support data intelligence." SingleStore has been on a fast track leading innovation around generative AI. The company’s product evolution has been accompanied by high-momentum growth in customers and surpassing $100M in ARR late last year. SingleStore also recently ranked #2 in the emerging category of vector databases, and was recognized by TrustRadius as a top vector database in 2023. Finally, SingleStore was a winner of InfoWorld’s Technology of the year in the database category. To learn more about SingleStore visit here. About SingleStore SingleStore empowers the world’s leading organizations to build and scale modern applications using the only database that allows you to transact, analyze and contextualize data in real time. With streaming data ingestion, support for both transactions and analytics, horizontal scalability and hybrid vector search capabilities, SingleStore helps deliver 10-100x better performance at 1/3 the costs compared to legacy architectures. Hundreds of customers worldwide — including Fortune 500 companies and global data leaders — use SingleStore to power real-time applications and analytics. Learn more at singlestore.com. Follow us @SingleStoreDB on Twitter or visit www.singlestore.com.

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