What can help marketers and advertisers drive better output when using AI? Steve Rotter, CMO at DeepL shares a few tips:

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Hi Steve, tell us about yourself, your time at DeepL and learnings from the B2B tech market in the last few years?

This is my fourth role as CMO within the tech world, and DeepL is my most exciting adventure yet for a few reasons. The rapid pace of the company, along with the appreciation for our product, both internally and from our customers has been incredible – we work with over 100,000 customers who tell us how much they appreciate the value we’re bringing to them and the pain points we’re solving, which are very real, critical, and widespread. It’s also just really exciting to be part of the incredible innovation that’s happening in the world of AI. We’re at a major inflection point in the industry when you look at how people and businesses are engaging with technology. It’s no longer a question of whether to use AI, but which AI to use – which puts us in a great position given the real benefits and ROI our Language AI platform delivers. This is also the dream from a tech marketing perspective, making it that much easier to connect with customers in a meaningful way and demonstrate the impact of our translation and writing tools effectively.

When it comes to learning from the B2B tech market, while it may sound cliché, I think what’s really important is making sure efforts focus on every aspect of the customer journey. For marketing teams to be effective and drive growth, they have to know customer pain points and how they discover and evaluate solutions. This can then inspire more targeted strategies that resonate with customers and address their needs directly.

How is AI in translation making an impact today and especially, a deeper impact to global marketers and advertisers for improved localization of campaigns?

Marketing and advertising are inextricably linked to language, which is how we communicate with consumers. It’s crucial to maintain brand consistency for successful campaigns—research shows that it boosts revenue by 20% or more. But achieving this consistency across borders and languages is tough, requiring not only linguistic translation but also cultural adaptation to ensure that messages resonate the right way in different markets. If advertisers and marketers don’t get this right, they’ll open themselves up to misunderstandings, wasted resources and missed growth opportunities.

Language AI, including the specialized AI-powered translation and writing tools we offer here at DeepL, is purpose-built to solve these challenges so that marketers and advertisers can easily create content that is coherent and culturally relevant across-borders. Whether they are localizing campaigns, branded in-store materials, or translating product names and terms, AI-powered translations make it possible for markets to maintain a company’s brand identity seamlessly across markets, enhancing consumer engagement on a global scale. This is not just a potential use case, either. According to our new retail whitepaper, marketing and advertising materials are among the most frequently translated content by businesses today. As more companies expand into new markets and look to reach new audiences globally, the importance of leveraging language AI tools for marketing and advertising will just keep on growing.

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Take us through some of the biggest names in the tech / SaaS industry who have used AI driven translation to improve local campaigns or other marketing performance?

Many big names across multiple industries including tech and SaaS are using DeepL’s Language AI platform to improve their communication and get better results in business and marketing. We now have over 100,000+ business and government customers worldwide, including 50% of the Fortune500, along with companies like Alza, Nikkei (owner of the Financial Times), Zendesk, Coursera, Deutsche Bahne, Weglot and more. The challenges of language barriers affect almost every type of business, driving broad interest in our AI-based translation and writing tools across most verticals.

Within the tech and SaaS space, Weglot – which provides localization and translation services to over 50,000 customers around the world — was an early adopter of the DeepL API, which they use to help companies build multilingual websites, translating billions of characters a month for companies all over the world. The accuracy and cultural relevance of these translations are essential for brand integrity, and the scale of our deployment highlights the effectiveness of our specialized translation service in addressing the needs of diverse businesses and markets

Alza, which is basically the Czech Amazon, is another great example of how DeepL is being used in the tech and ecommerce space. Alza uses DeepL to make sure their website content is properly localized in languages like English, Slovak, Hungarian, and German and French. Thanks to DeepL’s superior translation quality, Alza has saved thousands of euros per month in operating costs, as the brand’s human proofreaders spent significantly less time correcting DeepL translations, which means they can focus on more important projects.

Closer home, at DeepL, how do you use martech and AI to drive marketing and ad output? Specific takeaways for marketing peers reading this?

At DeepL, we’re operating at massive scale with over a hundred million monthly users, and we’re live – so we need a pretty powerful martech stack of external and internally developed solutions to monitor and manage that scale. One of the biggest areas we have invested in is data science and monitoring, to understand the weekly ROI of every ad spend in every region. As an AI company, everything we’re doing is data driven – including our marketing initiatives, where insights can help us make informed decisions to optimize our campaigns and increase our overall marketing effectiveness.

We’re also using martech to help customers see the value they’re getting from deploying DeepL. We’ve integrated our core platform data with Hubspot so that we can easily highlight customer usage metrics. This gives us a ton of valuable insight, and is something I would certainly recommend other tech marketers do – it gives us insight into usage patterns, customer satisfaction so we can thoughtfully tailor our strategies, identify up-sell opportunities, and generally build more effective campaigns and stronger customer relationships. Another critical martech strategy for us has also been improving our content strategy with DeepL. We’re live across over 220 markets and have built out a high-velocity localization team to ensure that everything we produce is in the language our customers care about.

Can you share a short list of some of your most preferred martech from around the world and why? 

Of course, DeepL for localization and perfect writing! Within the realm of localization, Weglot, I mentioned as one of our customers, is also a great go-to for on-the-fly website translation. Beyond these, there are many martech solutions I find valuable. These include email marketing automation solutions, content marketing tools, and data analytics platforms – which all provide thoughtful integrations of technology to assist with the various role responsibilities of marketing professionals.

Five top marketing tips you’d like to share here before we wrap up?

I’ve found the following three to be the most consistently effective over my two decades in the tech world:

1. Use data as your north star. Don’t rely on guesswork to drive impact. In the start-up phase, test different marketing strategies, and then collect, analyze and use the data that comes from them – this is how you find market fit and what works. Marketers should also be keeping an eye on things like conversion metrics, customer behavioral data and feedback, general market trends, and social media analytics. This data will be incredibly valuable to make strategic marketing decisions, refine your messaging, and ultimately help support the growth of the business.
2. Embrace iteration. In fast-paced industries like AI and tech, small iterations on existing marketing ideas can have an enormous impact. This is especially true if you’re a marketer at a hyper-growth startup and need to be economical and see results quickly. If something isn’t working, rather than completely overhauling your strategy and starting from scratch, consider making quick, agile and incremental updates: refine content strategies, tweak SEO, and so on.
3. Fail forward. It’s so important that teams and leaders cultivate a marketing culture that encourages experimentation and does not shy away from failure. Implementing a test-and-learn approach will provide teams with the autonomy to think innovatively and make adjustments in real-time based on their learnings, driving innovation and results.

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