Cost optimization

Kiss, Marry, Ignore: Assessing Your 2025 Sales Stack with Yuriy Zaremba

It’s budgeting season, and everyone is figuring out how to allocate their hard-earned funds to improve efficiency in 2025.

The year 2025 is shaping up to be extraordinary. AI is everywhere, driving us to optimize workflows and achieve more with less. On one hand, it empowers us to do just that. On the other, tighter budgets force companies to prioritize AI investments over other areas.

Sales teams are no exception. There’s been a surge of experimentation with AI sales tools, accompanied by significant hype and debate over their actual impact. How can we find the digital solutions we need while avoiding the pitfalls of overhyped technology?

To tackle this question, I teamed up with Yuriy Zaremba, CEO of AISDR, for a live Q&A session. Together, we explored strategies for optimizing sales tech stacks in 2025. If you missed the event, don’t worry—you can watch the replay or read key takeaways in this article.

1. How to avoid overlaps in the sales tech stack, with so many tools promising the same?

There are two approaches that vendors take: point solutions vs. all-in-one solutions.

The selling point of point solutions is that they focus on a specific area of the sales process. Therefore, you should expect better results with their product compared to an all-in-one solution.

All-in-one solution vendors argue the opposite: you don’t need those disjointed sales stacks, or “Frankenstack.” Instead, you can have everything on one platform, perfectly integrated.

How do you choose? There are two ways to think about this question:

  1. Would a point solution fit well into my existing stack to deliver maximum value? Or, if I don’t have enough pieces of the puzzle to derive maximum value from this point solution, maybe I should explore an all-in-one solution, which—rather than addressing a single pain point—delivers the entire workflow.
  2. Do you already have some tools for the same job? If yes, the switching costs might be too high compared to starting fresh. You can think about an existing tool with one critical feature that works well as an anchor. If something complementary comes along, you can add it to your stack to cover other needs.

So, you either start from scratch with a new all-in-one solution, or you add very narrow but high-performing solutions one by one, calculating the ROI for each.

2. What are the strengths and limitations of AI tools for sales? 

The first thing that comes to mind when you think about AI in sales is tools for email outreach. But that is a much broader topic. Through the experimentation we can see the following:

Where AI Shines

  • Transcribing and summarizing sales calls with precision
  • Automating follow-up nurture sequences based on call content
  • Qualifying inbound leads through conversational email interactions
  • Researching and identifying ideal prospect profiles
  • Generating high-quality outreach messaging
  • Creating interactive video demos and advanced website FAQ chatbots

Where AI Falls Short

  • Fully understanding nuanced product-market fit
  • Replicating genuine human emotional dynamics
  • Handling complex, context-rich human interactions
  • Creating truly unique conversation experiences
  • Replacing deep human relationship-building skills

The key is viewing AI as a capability enhancer: it handles repetitive tasks, collects context rapidly, and gives sales professionals more space to do what humans do best—build genuine connections and deliver unique insights.

The future looks promising, but for now, the goal is to make humans “superhuman” by leveraging AI’s strengths while preserving the irreplaceable human touch.

3. What are the most common traps of AI tools?

In general, it’s frustrating how some tools use AI for the sake of AI—just to drive up prices without offering a specific use case to prove its value. However, there are a few specific scenarios worth noting.

Hidden Costs

Sometimes, AI features are bundled into subscriptions without an option to turn them off. These features often add costs on a per-usage basis, so it’s important to be mindful of how many requests you make. Otherwise, usage can pile up unexpectedly, potentially tripling your bill.

If you commit to an annual subscription, it’s even trickier—you have no way to forecast the total cost if usage fees for AI are involved. Despite this uncertainty, you’ll still be required to pay. If you request a refund, you may find yourself referred to the terms and conditions, where you might be unpleasantly surprised by the refund policy.

When paying for usage, a particularly useful feature is the ability to set a spending cap. This ensures you know the maximum amount you’ll pay for AI, and you’ll receive a notification when you reach that cap. Always make sure to read the usage policy thoroughly before signing any contracts to understand what you’re actually committing to.

Termination Clauses

Another concern is what happens to your data after the contract ends. Will your data remain in their system indefinitely? Can you export it? Some vendors include very complex break clauses, making it hard to leave.

Auto-renewals can also be a problem. Many contracts require you to notify the vendor of termination up to 90 days in advance. If you remember to cancel only 89 days before the renewal date, you’re too late—and the vendor gets another year of revenue.

Vendor Lock-In

Another issue is being locked into a long-term contract for an unproven solution. While there may be opt-out provisions, they’re often buried in the fine print. Additionally, most of the opt-out period is spent configuring and launching the tool, leaving little time to assess its effectiveness before the opt-out window closes.

To make matters worse, vendors often price annual plans attractively while setting monthly prices at five times higher to nudge you into a long-term commitment.

To protect yourself, consider negotiating additional clauses in the agreement. For example, include terms that allow you to request a refund if you’re dissatisfied with the product, if certain features fail (e.g., “ABC breaks”), or within 90 days of purchase—essentially giving you a one-quarter trial period.

4. Where do AI tools sit in organizational structures in 2025?

AI tools are finding their place in various departments based on their specific functions. For instance, marketing teams often manage autonomous AI tools, particularly those used for email campaigns and lead generation.

Sales-oriented tools, such as email co-pilots and prospect research platforms, are typically overseen by revenue operations teams or SDR (Sales Development Representative) management. According to AISDR’s first-party data, companies spend an average of about $3,500 per sales rep on such tools.

However, functional department heads aren’t the only decision-makers or owners of AI tools, particularly in large corporations. In these organizations, individuals with titles related to AI or digital transformation often take charge of the AI experimental budget—a budget that many companies are actively allocating and managing today.

5. What sales tasks to automate and what to leave to humans?

Automation is ideal for repetitive, time-consuming tasks like email creation, LinkedIn outreach, and initial contact channels.

However, sales professionals still perform a lot of routine work during prospecting. They read through information, conduct research, build narratives, craft cases, and bring them to life. Despite this, few people consider these tasks suitable for automation.

Additionally, the actual buying experience—such as demo calls—shouldn’t be automated, except in scenarios involving self-service onboarding. While customers might self-onboard or interact with an AI avatar or chatbot for affordable products, high-stakes interactions require a human touch. 

Trust-building becomes especially crucial for deals exceeding $50,000, where personal connections and emotional understanding are key to success.

6. How can I negotiate subscription prices for AI software?

You have to understand that some vendors operate very high-margin businesses. For example, margins for cloud services are exceptionally high.

If you examine Amazon’s profit and loss statement, you’ll see that the highest margins and profits come from AWS. This means there’s often room to negotiate a good discount since they have significant margins to work with.

However, negotiating directly with big vendors like Amazon can be challenging. Instead, you should approach resellers—partners who have volume advantages and can offer you discounts through reserved instances.

Another strategy that’s especially relevant for AI vendors is taking advantage of promotional programs. These programs often provide free credits to encourage adoption within your company, and resellers can help you access these opportunities.

A classic negotiation tactic is mentioning competitors during discussions. This applies pressure on the vendor to win your business. By naming specific competitors, you can often secure better conditions, such as an extended trial period—sometimes two to three times longer than standard.

Timing is another effective strategy. At the end of the month, vendors are often eager to close deals to hit their quotas, which puts you in a better position to negotiate favorable pricing—especially if you’re dealing with salespeople.

These tactics can help you save significantly. However, if you prefer to delegate negotiations, Spendbase can handle it for you. The best part is that Spendbase charges no upfront fees. Instead, they take 25% of the savings they secure for you, making it a risk-free option.

7. Is performance-based pricing the only valid option for AI?

Performance-based pricing works best for tools directly tied to revenue generation or cost savings. This model allows you to rely on measurable business outcomes, such as time saved, deals closed, or operational efficiencies gained.

For example, how would you apply performance-based pricing to a tool that manages contract lifecycles? Its value is evident in how it streamlines the approval process. If the time required to approve contracts is significantly reduced, more deals can close in less time, providing a clear and measurable impact on revenue.

While not strictly performance-based pricing, selecting a vendor that can clearly explain how their pricing aligns with ROI is a solid approach. A vendor’s ability to connect their solution to tangible business outcomes can make their offering more compelling.

That said, not all software can adopt this pricing model. Tools like collaborative platforms, for instance, have value that is harder to quantify. You can’t directly attribute revenue to tools like Notion. Instead, their impact is typically measured through metrics such as adoption rates or net promoter scores, which offer insights into user satisfaction and engagement rather than direct financial outcomes.

Takeaways

Let’s summarize what Yuri and I discussed in response to the tricky questions from the audience. In the recording of the Q&A session, you’ll find insights on the following topics:

  • Current limitations of AI and how to leverage the tools effectively without getting caught up in the hype.
  • Hidden traps in sales tech contracts that could be costing you big time, and the simple negotiation tactics to avoid them.
  • Why the org structure for AI tools in 2025 may surprise you and how to position your solutions accordingly.
  • How much salespeople spend on tools they barely use and how they could have avoided that.
  • Subtle SaaS vendor negotiation tactics that can save you thousands and you’ll never pay the full price again.

In the recording, we dive into detail and share examples to support our perspectives—it’s definitely worth a watch.

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