Gone are the days when marketers relied solely on a shotgun approach to win over new customers. With the explosion of data and the availability of technology to extract new business insights, messages now are more targeted, and customers are being reached in the channels they prefer.
Despite this development, there is still a huge divide between marketing for B2B and B2C customers. For one, the sales cycle in B2C is much shorter, almost like an immediate sale. However, data is transforming the entire marketing process with new ways to understand consumers, whether corporate or individual.
Stephanie Buscemi, Chief Marketing Officer of Confluent, sat down with Frontier Enterprise to discuss the evolution of the marketing landscape, and how Confluent is positioning itself amid all the market movements.
What was your transition like, from your previous companies up to your current role at Confluent? How has marketing evolved during that period?
I’ve been in marketing for 25-30 years, and then assumed marketing leadership roles, mostly on the application side. I joined Confluent almost three and a half years ago because we all saw the explosion of data, and dealing with it became a bigger problem. While I was at Salesforce as CMO, I started to see that we had so many applications out there, yet the applications are only as good as the data.
Back then, I became a student of understanding how, as a marketer, we think about data and use it to create personalised experiences. The biggest evolution has been the role of data for marketers. There’s been a channel hype cycle: direct mail a long time ago, then email, social media, and mobile.
Now we’re multichannel, and there’s always something new added to the menu of channels. However, it’s all about the underlying data. At Salesforce, I started to think a lot about how we deal with data differently, not just as marketers, but as companies.
For marketers, the introduction of data probably happened 15 years ago, focusing more on marketing performance rather than experience. It wasn’t used in a closed-loop way to inform the experience. To better personalise and do marketing more efficiently and effectively, we need to determine what the next best action is as a marketer, especially in terms of integrating AI. The biggest shift has been the role of data: from being just about performance to being equally important in driving engagement and creating a better experience.
B2B tech is so much predicated on a direct selling model, which is so expensive. If you consider an account executive, it’s an expensive proposition for a company. As marketers, we had a traditional model of putting things out in the market across different marketing channels, seeing what comes in, and giving it to the direct sales team to convert. Now, we’ve realised that people have different formats and ways they want to be engaged.
An example for a marketer is product-led growth. I lead our product-led growth, focusing on building self-serve motions that don’t require a salesperson. Today, it’s all behaviour-based. Historically, there was an MQL (marketing qualified lead), and now there’s the notion of a PQL (product qualified lead), which is all trigger-based behaviour models. We push you, through AI assist, towards the next best action.
If you think about that 10-15 years ago, a lot of bodies would have had to engage. About 25-plus years ago, we relied on direct mail and waited to see if somebody got it in snail mail. Now, we use product telemetry data and web data to inform our campaigns. Marketing will always be a combination of art and science, but now we have so much more at our disposal to create a better experience and help companies drive marketing at scale more efficiently.
With the availability of granular metrics, how do you see the role of product managers and marketers evolve? Do you see that closed loop in B2C similarly happening to B2B?
In my opinion, I’ll always be learning from B2C. On a personal note, I get invited to many B2B tech marketer events, and I go to a few, but I actually prefer to attend events outside the industry and go to B2C, because it infuses new ideas. Sometimes, when I’m around B2B marketers, it feels like an echo chamber, so I purposely seek out B2C insights. I will always follow what’s happening in B2C and look for applicability on the B2B side. We’re getting better at creating experiences and engagement for individuals, but at the end of the day, maybe there’s someone out there mastering that at the account level.
At the consumer level, someone’s trying to sell you an item like tennis shoes, and it’s for you. You’re the single evaluator — it’s your preferences and likes. When buying a data streaming platform in an enterprise-size organisation, there could be a dozen people involved in the decision. Hence, while we’re marketing to them and creating better engagement and experiences, what intelligence are we able to gather collectively at the account level to understand overall engagement?
We talk to Kafka developers, then to data scientists and tech execs. I can think of all the people within an organisation and have some level of assessment of our penetration. But do I have a way to collectively look at the overall sentiment? I think we’ll get there, but it’s complex.
Speaking of B2B, a lot of marketers have said that the decision-making process on the end user side has evolved over the years. Do you also see the same thing?
I do, and I’ll give an example. The way people are buying technology has changed. When I was at SAP a long time ago, a CIO might make or break their career on purchasing SAP. That’s how it was done for decades. Now, developers and engineers have a much stronger voice than they’ve ever had before. I no longer think anyone in a C-suite chair will buy something without knowing whether they will get adoption and usage.
Pick any company — you’d see a CIO come in, and it used to be much more top-down. Someone would buy everything, and then you’d find out later there wasn’t much adoption or usage. Maybe you got oversold, overbought, and now you don’t need it. Now, if you look at Confluent, we’re a consumption model, so you’re paying for what you use. It changes everything because success is predicated on usage, and I think that changes behaviour and who is involved in the buying decision.
What is Confluent’s market strategy in relation to open source adoption of Kafka?
As we expand into different countries, there are markets with higher open-source Kafka usage and adoption. It’s much easier for us to start and land in those markets because we’re already halfway there; they’re already using open-source Kafka. We don’t have to drive awareness or make the argument for streaming.
This doesn’t mean we won’t go to other markets. For example, Japan does not have a massive Kafka open-source community, but we have a business and a growing presence there. It is easiest to start in countries with high open-source Kafka adoption, and we know this because of our developer relations. These countries have our largest open-source Kafka communities. You can see this by the number of people who attend the meetups we run in those countries.
