1. When ticketing, payments, add-on sales, and reporting sit in one platform, where do you see the biggest marketing advantage?

To a degree, this is what marketers have been hoping for and what a lot of platforms have already promised. One real single source of truth, where the data points that matter for personalization, targeting and insight generation sit in the same place and finally add up to a clear picture of who your customer is – no more stitching.

The stitching cost is the part most people underestimate. Salesforce surveyed 4,450 marketing decision-makers for its 2026 State of Marketing report: 98% said they run into barriers with personalization, and data problems were the most common reason. Only around half of respondents said they had complete access to their own service, sales and commerce data. The constraint is usually that historical customer data sits across five systems that were never designed to talk to each other.

When ticketing, payments, add-ons and reporting sit in one place, that problem goes away. You see the whole transaction instead of fragments. A fan who bought two tickets, added parking, spent at the merchandise stand, and came back three times last season is now catalogued in one profile. Everything downstream gets easier because the input is finally clean. The same Salesforce study found that marketers working with unified data are 42% more likely to respond to customers in a timely fashion. That is a fairly plain description of the benefit of better input.

2. As more capabilities move into a single platform, which standalone marketing tools do you think will become less necessary?

I don’t think whole categories of tools become less necessary. Outdated technology comes under more pressure to adapt or die, but that is true with or without platform consolidation.

The landscape numbers point the same way. Scott Brinker and Frans Riemersma counted 15,505 martech tools this year, up from 15,384 in 2025. While these figures are flat on the surface, close to 1,500 tools were added and more than 1,300 disappeared. Two-thirds of the tools that fell out in the prior cycle were built between 2010 and 2020, so what looks like a plateau is actually a replacement cycle.

Our view is that the challenges faced by every event organizer, and almost every other company, are so unique that they have to build their own ecosystem and organize their tools around their individual business strategy.

Certainly, specialist tools with a sharp value proposition will keep their place, as will those generalist tools that are effective at supporting multiple strategic components.

3. Do open APIs and flexible sales channels give marketing teams freedom to build the customer journey they want? Where does that flexibility matter most?

Yes, definitely. Not on their own, but they are an important part of that equation.

I think it’s important to examine the question slightly differently because open APIs don’t give marketers the freedom to build the customer journey they want. Instead, they give them the flexibility to build the journeys their individual customers require. That is a different standard, and a harder one to meet.

Where it matters most depends on the type of relationship:

In B2B, it matters at the edges of the operation. The standard path is: browse, buy, receive the ticket. However, the value sits in a specific organizer’s needs, but no vendor roadmap prioritizes that for them. Real-life use cases are: A season ticket holder who wants to split a package with a colleague. A festival selling payment plans in one market but not another. A university that has to route donor conversion through its own advancement system. When each of those requires a support ticket and a six-week wait, the journey is dictated by the vendor’s backlog. When they can be built straight away, the journey is designed by the organizer.

Speed is the other half of the equation. Sales channels change faster than procurement cycles, and an organizer who has to renegotiate a contract every time a channel shifts will always be stuck a season behind.

In B2C, it matters where the decision happens. This is the part I find more interesting right now, because the platform where people decide to go to an event keeps moving. For a long time it was the organizer’s website. Then a lot moved to social. A growing share of discovery now starts with an AI assistant, and ticket buying is beginning to follow.

The infrastructure is being built quickly. OpenAI and Stripe published the Agentic Commerce Protocol in September 2025. Google and Shopify launched the Universal Commerce Protocol in January 2026 with Walmart, Target, Visa and Mastercard among the backers. The Agent Payments Protocol moved to the FIDO Alliance in April.

I would stay cautious about any timeline for success. OpenAI’s own Instant Checkout ran for about five months and closed in March 2026 with close to no sales. Walmart’s assistant converts at roughly 70% of the rate of its own site. The infrastructure is running well ahead of consumer behavior, and I don’t think anyone can predict the date when that will change.

Practically, this is a readiness question. If a venue’s inventory, pricing and checkout are addressable through an API, the tickets can appear in a new channel in weeks and step back out just as quickly if it doesn’t work. If they sit inside a closed system, the venue has to wait for its vendor to decide the channel is worth supporting, and whatever advantage there was in being early is gone.

There is a second reason I would flag to any consumer-facing marketer: A channel that you can only reach through someone else’s storefront is a channel where the consumer relationship belongs to someone else. You sell the ticket, but the record of who bought it, what they paid and what else they might be interested in sits with the intermediary. In B2C, that compounds quickly, and the flexibility completely loses its value if you don’t have any data or insights about your customers’ behavior.

4. AI is often discussed in terms of reaching new audiences. Where do you see the immediate opportunity in using AI to activate audiences you already know?

I would go further and say activating known audiences is the greater opportunity.

We all know how discovery of new audiences has worked so far. Algorithms take data points, infer a personality, and match that to a product or a campaign. It has real uses, and it clearly helps in a lot of industries: FMCG, automotive, real estate. But it has limits, and that limit is where marketing has to understand people at a deeper level to convince them to build a relationship with the company or event.

In live entertainment, the motives become so complex that inferred signals stop being predictive. What I liked on social media last week, or what I bought on Amazon last year, says very little about the following decision: my club is closing in on the league trophy for the first time, and my favorite band is playing their final concert, but the dates collide, and my circumstances allow for the purchase of one ticket. No amount of lookalike modeling gets that right.

What you can work with is what you know for certain. Someone bought. Someone attended. Someone lapsed. Someone upgraded. Re-winning that person, or growing their CLV through merchandise, hospitality or a membership tier, is a far more tractable problem than guessing about strangers. Salesforce found that 75% of marketers have adopted AI, while 84% admit they still send generic campaigns. That huge gap comes down to data access more than model quality.

That gap is what we are shrinking in two steps:

The first step is shortening the distance between knowing something and acting on it. As Simon Hennes, our CEO, puts it: organizers learn something about their audience with every ticket they sell, but acting on it has always been the hard part. Addressing this, in June, we shipped vivenu Engage, so a team can build an audience using live purchase, attendance and spend data and run the campaign from the same place. That means segments that update themselves. Discounts and fee waivers aimed at one group. Inventory released only to the people who earned the access. No export, no pipeline, no data team needed to ask a question. Forrester found that 78% of B2C marketing executives work with fragmented stacks, and in our industry, a lot of the lost time sits precisely in the gap between the export and the send.

The second step is creating the reasoning layer above it. At the end of July, we launched the vivenu AI Assistant together with Analytics AI and Campaign AI, which allows users to ask plain language questions against live data, segments are built from a description rather than a query, and campaign copy is drafted in the organizer’s own brand for a human to approve. Spenser Ayres at Stanford Athletics described it as asking about sales, revenue and customer behavior in plain language and getting answers from their live data in seconds. That sounds modest. In practice, it removes the two-week wait between a marketer’s hunch and someone with database access confirming it.

Those two design decisions matter more than any list of features, and they are what support the argument rather than just riding the trend:

Every customer’s assistant works only on that customer’s ticketing data. Nothing it learns about one organizer’s business is shared with, or learned from, another, and it runs inside the same security perimeter as the rest of the platform under SOC 2 Type II, PCI-DSS, GDPR and ISO 27001. If the premise is that the organizer owns the relationship, a model trained across everybody’s audiences would quietly contradict it.

The second is that it stays API-first, with an MCP server, so the same data and the same reasoning are available to whatever else the organizer runs. We are not asking anyone to move their marketing inside our platform.

Where I would stay cautious is about what this achieves. It reduces execution effort, but it doesn’t understand why someone picks one concert over another. Simon framed it well at launch: the point is to free people up for the part only humans can do, which is working out what motivates a fan. McKinsey puts the productivity gain from generative AI in marketing at 5 to 15%. That is meaningful, and it is not a strategy. The strategy stays with the marketer.

5. What does this shift mean for the MarTech stack? Do you see email platforms, CDPs, loyalty tools, and commerce layers becoming integrated with ticketing platforms or being consolidated altogether?

Business model-specific ecosystems still rule, but our own category is clearly moving. The industry is pushing us to become a commerce engine for live entertainment with core ticketing functionality inside it, rather than a ticketing platform with extras added on.

Where specialized tools carry real value, an integrated stack outperforms a consolidated one. Our work with WMT Digital at Stanford Athletics is the clearest example. It supports dynamic pricing at seat level, driven by live demand data. Just looking at basketball data, the system made roughly 872,000 automated price changes and eliminated 242 hours of manual work, equivalent to 26 working days in one season. Dynamic pricing accounted for 19.4% of its basketball ticket revenue. You can run dynamic pricing on our platform alone, and you can connect WMT to other ticketing platforms. That result came from both systems working together to meet the specific business challenge that Stanford Athletics was facing.

There are two areas where I do anticipate consolidation:

The first is single-application tools, email being the obvious one. Most of the differentiating capability there is reasonably easy for companies like us to copy and improve inside a more holistic platform. Ditto for platforms like HubSpot and Salesforce. Once that happens, there is hardly any value proposition left in a standalone tool – or at least the value of data consolidation is simply higher. So why run two? I expect a certain commoditization of core marketing capabilities like this.

The second is data platforms, like CDPs and DMPs. In essence, and I don’t mean this negatively, they are data aggregation and gateway tools. Yet two things work against that position. Security increasingly depends on controlling every access point to your own data, and every external platform adds complexity. Plus, the aggregation and routing work is getting much cheaper to build locally. The Model Context Protocol was donated to the Linux Foundation’s Agentic AI Foundation in December 2025 by Anthropic, Block and OpenAI, with Google, Microsoft and AWS behind it. When a team can wire that up themselves, arguing for an external data layer gets harder. To date, there are still scenarios where it is different, but it wouldn’t surprise me if that changes.

This category is already under pressure. Around 208 CDP vendors are in the market; six were acquired by the middle of last year alone, equalling the two prior years combined, and warehouse-native approaches are growing roughly six times faster than the rest of the category. While there will be a role for the function, the need for a separate product may not endure.

6. When evaluating a MarTech partner, how much weight do you now place on API access, data portability, and the ability to integrate with your existing stack?

We don’t do that evaluation, but I’ll answer from where we sit: As long as a partner does not expose our platform to risk, we are agnostic. Our customers make that decision, and we sometimes advise on what the right stack looks like for a particular business case. Those conversations have shifted with more organizers wanting complete control of their success. That translates directly into wanting to own and connect their own data. The values we hold on data ownership are becoming their values, and that is a large part of why our business is growing. It works more like natural selection than like a sales process.

If I were advising someone evaluating a martech partner today, I would say the weighting has changed for a structural reason. Growing a business in a difficult economy depends more and more on hyper-personalization and precise targeting, because it creates value for the customer and, in times of economic challenges, consumers maximize value. The data quality to support it is only achievable at the highest levels of connectivity. So API access, export rights and portability are no longer procurement hygiene. They set the bar for what your marketing can become over the next five years.

7. Where do you think marketing teams in live entertainment are still leaving value on the table when it comes to their customer data?

Most organizers have a fairly precise idea of what they are leaving on the table, and the cases we see are all very different. If I had to generalize, I would say the value is loyalty. Specifically, orchestrating the entire journey so everything around the event becomes as interesting as the show or the match itself, because it was tailored to that person.

Take a venue. Today, fans say “we’re going to a Taylor Swift concert.” A venue that invested fully in this could flip that to “we’re going to the arena tonight, and Taylor Swift is playing.” That’s a small wording change, but commercially it is the difference between being a space that hosts events and being a brand with an audience of its own.

The money is visible in the parts of the industry that have already invested in this. Live Nation reported this year that at newly opened amphitheaters, enhanced on-site offerings are driving premium revenue close to 75% higher than at comparable venues. That is physical investment. The data equivalent costs far less and is a largely untouched opportunity.

8. If organizers gain ownership of their audience and data, how do you expect the role of the marketing team itself to evolve?

It becomes what everyone studying to be a marketer expects the job to be: spending most of their time on creative strategies that create mutual wins, better experiences for the customer and more money for the company, with insight generation and execution becoming easier, quicker and more reliable through ownership and the application of AI.

I would add one thing. Data ownership also changes accountability. When the data is yours, weak results can no longer be explained by a vendor’s reporting limits. That is uncomfortable, and it is the right trade.

9. When purchase, payment, entry, and on-site spending data are connected, how does that change the way your team thinks about the customer journey?

It makes it more personal. It should get to the point where the team can close their eyes and visualize the people in front of them. The modern version of personally knowing your customers is the way it used to work when the person selling knew the person buying.

We then move from inferred profiles and personas to something closer to full human discovery. You’ll still have an audience segment called parents. Inside it, you’ll be in a position to see Barbara, who parks close to the venue because she has a toddler with her and rents a stroller once she is inside, while her husband is already in the fan shop spending the merchandise allowance from their membership tier on the pre-flocked jersey you had sitting there for them since yesterday.

You still won’t meet them in person. You are still a marketer addressing bigger masses overall. But the experiences you create make them feel as if they have their own personal experience assistant.

I like the idea of marketers thinking this way now, in the age of AI, because for the first time it doesn’t read like a visionary promise to dream about. It’s something any serious company can achieve if it invests now. It might take 12 to 24 months, but I truly believe in the result.

Author bio

Standard, 55 words.

Maik Erkelenz is Global Director Marketing at vivenu, the API-first ticketing platform that lets event organizers own their audience data outright. He spent nine years as a business consulting director and data protection officer before moving into SaaS, and works at the intersection of CX, CRM and data security. He also serves on the board of his local sports club, TV Osterath.

Short, 28 words.

Maik Erkelenz is Global Director Marketing at vivenu, an API-first ticketing platform built so event organizers own their audience data. He writes on CX, CRM and data ownership.

Long, 95 words.

Maik Erkelenz is Global Director Marketing at vivenu, the API-first ticketing platform used by sports programs, festivals, venues and cultural institutions to run their own commerce and own their fan data outright. Before joining vivenu he spent nine years as a business consulting director and data protection officer, most recently at CROSSMEDIA, which shapes how he approaches marketing technology: data ownership as the precondition for personalization rather than a compliance line item. He writes and speaks on CX, CRM and the martech stack in live entertainment, and sits on the board of his local sports club, TV Osterath.

Source notes for the editor

• Salesforce, State of Marketing Report, 10th edition, 2026. 4,450 marketing decision makers, surveyed October to November 2025. Figures: 98% hitting personalization barriers, 75% AI adoption, 84% still sending generic campaigns, 42% unified-data advantage.
• Martech landscape 2026, Scott Brinker and Frans Riemersma. 15,505 tools, up from 15,384; roughly 1,500 added and 1,300 removed.
• Stanford Athletics x vivenu x WMT Digital, published case study. Basketball: 872,000 automated seat-level price changes, 242 hours of manual work removed, 19.4% of ticket revenue from dynamic pricing, 24% average ticket increase. Football: 3.9 million price changes, 194 hours, 12% of revenue.
• CDP market: 208 vendors as of July 2025, six acquisitions in mid-2025, warehouse-native vendors growing at 7.8% versus a 1.3% category average.
• Model Context Protocol donated to the Agentic AI Foundation under the Linux Foundation, 9 December 2025, by Anthropic, Block and OpenAI.
• Live Nation Entertainment Q2 2026 results. Premium revenue at newly opened amphitheaters is close to 75% higher than comparable venues.