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Mastering Lead Generation for Financial Service & Product Industry

Author: Ciente Editorial Team

Mastering Lead Generation for Financial Service & Product Industry
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Mastering Lead Generation for Financial Service & Product Industry

Mastering Lead Generation for Financial Service & Product Industry

Marketing for the finance industry is not the same as other sectors. And while the same advice can help you set up it takes something else to win.

Imagine losing a million dollars overnight. If that doesn’t send a chill down your spine, what will?

But for those who do, this mishap is a tragedy.

This is what the buyers of any fintech have to deal with.

The possibility of losing money through no fault of one’s own. To wake up one day with their secured funds empty.

To say trust drives lead generation is an understatement. Building this authority requires content marketing strategies that work in the financial industry to address specific pain points like security and compliance. Without trust, the buyers would use their existing solutions till kingdom come. And maybe even then, they’d stick to what works, because our current systems give rise to uncertainty while simultaneously promising its elimination.

Financial buyers are tired of these paradoxical lies and move to organizations that prove they can be trusted or to traditional banking institutions- deeply embedded in the world economy.

If you want to generate leads for your financial or FinTech org, the question is, how do you disrupt the status quo and be considered the safe choice over traditional ones?

There is a leverage here, and it’s called convenience. And the buyers are all about it.

Why do FinTech and Financial services need lead generation?

Lead generation has been getting some bad rep lately. It’s perceived as a way to farm people’s information for data. Especially when confused with outdated traditional lead scoring approaches. There’s a reason buyers have become self-directed and choose to engage way later in their buying cycle.

Lead generation has become synonymous with lead lists, which it is not. High-performing firms treat it as a structured lead generation framework, not a database dump. While high-performing organizations have their own definitions of a lead, lead generation does have a broad definition.

It is the process of gaining the interest and trust of a potential buyer, and turning them (the people) into paying customers.

By this definition, FinTech and the financial services industry don’t just need lead generation but have to sustain themselves through it. Think of this: your SDRs are on-call (cold) and you try to explain what your organization does, and midway, they stop and say, “But our existing solution does this, too. Why do we switch?”

That is a rhetorical question.

They don’t or can’t switch because of the massive changes involved in using a financial service or tech.

There’s a lot of red tape that will hinder it, even if the buyer is genuinely interested in what you have to offer. Lead generation can bypass this by building trust before your SDRs even reach the prospect, as shown in these AI-powered lead generation strategies.

In fact, the buyer will reach you when their need for your solution eventually arises. Your SDRs will have to act as consultants here.

Strategies to Drive Quality Leads for the Financial Industry

Let’s divide this into two parts.

  1. Financial Services
  2. Fintech

Between the two, FinTech has an advantage being the new-age tech, especially after ’08. The crash made people realize just how volatile the banking sector can be and that people needed alternatives. Ever since then, financial services, especially banking, have not yet recovered this trust.

People look to private organizations that mitigate these damages. Instead of lining up in a queue to withdraw their savings, they are secure from the economic downturns in privatized solutions.

For example, Revolut, a tool designed to help you spend and save. But their real promise lies in keeping your money safe.

But the real promise lay in its transparency and becoming a champion of underserved markets.

Something traditional services took a long time to position themselves as.

So, let’s talk about financial services first.

Lead Generation Strategies for Financial Services

Trust is a vital tenet for marketing. Ask any marketer, and they’ll tell you that first and foremost, marketing is all about communicating trust and building a relationship with it as the base.

For financial services, this tenet is magnified. It’s gospel.

The involvement of money means that for people investing in your services, you are a high-risk option. Imagine selling that to a client.

“Hey, you don’t know us, but we’d like to replace your current insurance provider, and maybe we’re not malicious. You can trust us with the livelihood and lives of your employees. We won’t cheat you. Promise!”

If only that were so easy.

1. Building a relationship.

Let’s assume a few things first,

  1. You have a client base, because if you don’t, you need customer acquisition, not lead gen. And customer acquisition requires a sales-led approach first.
  2. You know what you’re doing marketing-wise, i.e., your end goal- X amount of sales. You must have case studies, whitepapers, blogs, email marketing, advertising, and all the basics that need not be outlined because they come before lead generation.

The above two assumptions are also your first steps. But rarely does a financial service start without a client.

While you must have heard about thought-leadership, building relationships is a bit different. It involves inviting your core buyer to check what you have to offer. Many B2B buyers feel their sales calls are transactional.

Here is the opportunity for your brand and solution to try something different. Through sales or through marketing, build a rapport as a problem-solver. Supported by disciplined inbound lead generation systems.

This involves: –

  1. Being active where your buyers are- email, social media, ads, on-calls, etc.
  2. Listening to their problems and asking for market feedback (this is a tough one because it means divesting effort from direct sales and also because the market doesn’t have time to answer).
  3. Asking your sales teams to listen to the problems and using social and email to craft messaging relevant to real-time buyer problems.

This builds credibility. And it is a strategy that is easier said than done. But as you would know, people in finance are cutthroat. And what do cutthroat people like?

A little bit of ROI, honesty, and genuine interest in solving financial problems.

2. Understanding your context.

This is a point that might be universal to all lead generation strategies. To: –

  1. Understand the market’s history with your services
  2. Your context in the current market (which shapes marketing messages).

This step assumes you have a clear vision of your audience. Developing detailed customer personas for financial services is essential to ensure your messaging resonates with the right decision-makers. If you or the top management don’t know that, then the sharks in finance are going to defeat you.

The reason this step is so important is that it will shape the way your marketing messages sound and your SDRs talk- shaping market perception. For example, let’s say you are a bank selling its salary account to an SME.

The SME has been working with bank XYZ International for a long time. There have been hiccups, yes. But they’re fine with how the bank has helped its employees. But you know the way the SME is growing, the bank XYZ won’t be able to handle the growth.

There aren’t enough insurance plans, and there’s no scope for any 401 (k) or other pension plans beyond government-sanctioned ones.

Your context is this: We safeguard you and your employees while you scale.

This is how context shapes marketing. Won’t you be interested after seeing this message?

3. Leveraging Loyalty.

Why would a buyer change providers? Even in the above example, the SME, now growing, can push the bank to grow, too. After all, loyalty is a major factor in the finance sector. It is a facet of trust.

And while businesses do switch for convenience and growth, they might not give up their existing vendors because they have built relationships. Penetrating new markets is easier, but when competition is at its peak- which it is for financial services- it isn’t.

The conversations you have with your leads will go nowhere.

There’s just too much. You’d have to understand their process, internal money flow, operations, taxes- everything. And let’s not forget the policies the government has imposed on both entities, which are stringent again, because money is involved.

The business has too much to lose in switching. How would you convince them otherwise?

You turn the playbook- you show them the cost of not switching; of loyalty failing when it matters.

Let’s drive this home with an example that does not paint financial services in a good light but also presents an opportunity.

The PPP Loan Disaster

The PPP Loan Disaster must be fresh in many business owners’ minds. COVID-19 struck, and many businesses feared they would go under, but when the Paycheck Protection Program was set in motion, many large banks like Wells Fargo and Bank of America prioritized their bigger clients.

The funding ran out in May, leaving small businesses hanging out to dry.

Tragic.

Loyalty became a cost for SMBs and SMEs who couldn’t survive the harshness of COVID-19 and the apathy of the financial service industry. Many sought refuge in Fintech solutions.

And this is where lead generation transforms from data to a human-human connection. The trick is in loyalty and staying with your customers in turbulent times.

If you make that promise and stand by it, your service would probably dominate the market for years.

For marketing messages, this could take the form of risk-assessment reports, case studies, blogs, outreach, etc. But those are channels and methods of conveying your core message. And the core message for financial services is clear: deliver on the promise of monetary security.

Because FinTech is doing it better.

Lead Generation Strategies for Fintech

For leaders in FinTech, the above section must have made it clear that you have advantages over traditional financial services. So your competition becomes other FinTech solutions, and while you may have trust for the time being, your competition is leveraging something greater: convenience.

Let us preface this part with a little disclaimer: Lead generation is somewhat universal in its methods of omnichannel and multichannel experiences, email marketing, and outreach.

Let’s focus on a real strategy. It has three facets:

  1. Design
  2. Integration
  3. Positioning

a. Design.

In product, design is vital and attention-grabbing (a crucial component of lead-gen!) But beyond that, design informs one thing: Is it easy to use?

Whether it’s the ease with which your client connects to or opens a bank, or the ease with which their finances improve. That’s why Revolut has become such a hot commodity.

Their website on its own screams good design. And if the website is that good, the product can’t be that bad, is what people usually think. And what do you know? Revolut is a great app for personal and business use alike.

The question for differentiation is: Can you build trust through design?

This is what brings leads in. The workflow looks something like this:

Great Idea→ Great Design→ People like Lenny Rachitsky (product people) talk about how great your product and design philosophy is→ organic leads and traffic.

Yes, that is what it looks like for the product ecosystem to thrive. Aesthetics and function are drivers of inbound lead generation. Especially when amplified through strategic lead magnets.

b. Integration.

Which naturally leads to integration. Great design doesn’t mean the UI is fantastic; it means that the APIs integrate seamlessly with other existing stacks and workflows.

This is a major USP for most organizations, and the one with smooth integration will be the final choice. Making precise targeted lead generation essential for tech-forward buyers. Whether a business’s AI system, banks, and other workflows can integrate your product will decide how viable your solution is for them.

c. Positioning.

This leads to the final strategy in FinTech lead generation. Positioning your product for the context of the buyer.

Here’s an example for this, too. UPI in India.

The Indian market is a bit different; adoption of tech takes time there. But PayTm, a Venmo-esque app, started gaining traction. And then the Indian government launched the UPI, a universal payment interface, and began the greatest FinTech boom in history.

The main point was to make transactions transparent in a country full of corruption.

Did anyone expect Google Pay to become such a dominant force in the market? But it did, and that’s because Google understood the market and its position. They saw people used PayTM and a native app called PhonePe and conquered the Indian transaction market.

Even now, the two FinTech apps are competitors for a large market. And they show all three facets outlined.

  1. Intuitive Design- they pick up QR codes faster than any app, show bank balances, payment history, spend, etc.
  2. Robust Integration – They are secure and linked to bank accounts.
  3. Positioning- Finding and capturing an emerging market.

This made it so that people flocked to these apps and not vice versa.

This went beyond lead generation and directly into market adoption. This is a clear advantage that products have over services- people can use it and experience the product before adopting it completely.

Lead Generation in finance is complex because it’s abstract.

Yes, there are many abstractions in finance because money is abstract and involves many restrictions, government-mandated regulations, and factors of trust.

It’s red tape everywhere. And lead generation needs to reflect that to gain the buyer for the long term. Without this, financial services become too risky, and FinTech becomes noisy and irrelevant.

It is a lot of work, but you don’t have to do it alone. Ciente has served finance and FinTech since our inception and has understood the principles that drive sales, trust, and growth.

And trust us, without these, a business in the finance industry cannot survive.

Today's rapidly growing digital-first landscape has elevated concerns around data privacy and security. From marketing to the SaaS landscape, this trend has etched itself into the future rulebooks. The thing is, data security isn't a trend. It's a gross dilemma. In recent developments, Hitachi Solutions has covered new heights. It developed a solution to overcome significant challenges in cloud interoperability across the public sector. All in a creative collaboration with Microsoft. Government bodies hold highly sensitive information, of citizens and businesses alike. And your phone numbers and physical addresses are merely the tip of the iceberg. These could easily be a target point for nation-states and cybercriminals. For a body with such a valuable database, data security often goes overlooked. Or at least, not as spotlighted as it should be. Why so? It's substantially due to immense budget constraints, outdated systems, a shortage of talent, and, significantly, the interconnected nature of govt. Services. These elements have hijacked the public sector's progress. These gaps have made the government organizations too vulnerable to hacking. So, Hitachi Solutions and Microsoft have engineered an innovative fix. One that retains the full value of Microsoft's AI tech to unlock more modern and responsive solutions for UK citizens- Secure multi-cloud operability for public institutions to help safeguard their data and accelerate responsiveness. Its chief capabilities comprise: • Private access within Microsoft business apps, AWS, and GCP databases. • Bi-directional data integration without any public internet exposure. • Zero-trust and scalable infrastructure that aligns with the UK's security frameworks. • Maximum use of existing assets doesn't facilitate data duplication. This innovative feat will aid the UK's public bodies in sharing and transferring sensitive public data by connecting systems, while ensuring compliance with requirements. The workflows and data that remain across different environments, such as GCP, Azure, AWS, and Oracle, can now be amalgamated into one. Expensive cloud migrations, primitive tools, and manual workloads are a hitch in the government's cloud operability. But Hitachi's solution is a saving grace. This secure multi-cloud connector facilitates Microsoft apps to access data across GCP, AWS, or Oracle environments in real-time. This is achieved through a private connection that doesn't require any duplication or public Internet access. "The flexibility to use the right tool for the job regardless of where data resides is essential for modern, efficient public services," chimes in the Commercial Director, Government for Hitachi Solutions. Hitachi Solutions' Secure Multi-Cloud Connector Transforms Govt. Cloud Interoperability
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Hitachi Solutions’ Secure Multi-Cloud Connector Transforms Govt. Cloud Interoperability

Hitachi Solutions’ Secure Multi-Cloud Connector Transforms Govt. Cloud Interoperability

With the public sector more vulnerable to hacking, compliance came before innovation. But Hitachi’s new solution might just be the catalyst for change.

Today’s rapidly growing digital-first landscape has elevated concerns around data privacy and security. From marketing to the SaaS landscape, this trend has etched itself into the future rulebooks.

The thing is, data security isn’t a trend. It’s a gross dilemma.

In recent developments, Hitachi Solutions has covered new heights. It developed a solution to overcome significant challenges in cloud interoperability across the public sector. All in a creative collaboration with Microsoft.

Government bodies hold highly sensitive information, of citizens and businesses alike. And your phone numbers and physical addresses are merely the tip of the iceberg. These could easily be a target point for nation-states and cybercriminals.

For a body with such a valuable database, data security often goes overlooked. Or at least, not as spotlighted as it should be. Why so? It’s substantially due to immense budget constraints, outdated systems, a shortage of talent, and, significantly, the interconnected nature of govt. Services. These elements have hijacked the public sector’s progress.

These gaps have made the government organizations too vulnerable to hacking.

So, Hitachi Solutions and Microsoft have engineered an innovative fix. One that retains the full value of Microsoft’s AI tech to unlock more modern and responsive solutions for UK citizens-

Secure multi-cloud operability for public institutions to help safeguard their data and accelerate responsiveness. Its chief capabilities comprise:

  • Private access within Microsoft business apps, AWS, and GCP databases.
  • Bi-directional data integration without any public internet exposure.
  • Zero-trust and scalable infrastructure that aligns with the UK’s security frameworks.
  • Maximum use of existing assets doesn’t facilitate data duplication.

This innovative feat will aid the UK’s public bodies in sharing and transferring sensitive public data by connecting systems, while ensuring compliance with requirements. The workflows and data that remain across different environments, such as GCP, Azure, AWS, and Oracle, can now be amalgamated into one.

Expensive cloud migrations, primitive tools, and manual workloads are a hitch in the government’s cloud operability.

But Hitachi’s solution is a saving grace. This secure multi-cloud connector facilitates Microsoft apps to access data across GCP, AWS, or Oracle environments in real-time. This is achieved through a private connection that doesn’t require any duplication or public Internet access.

“The flexibility to use the right tool for the job regardless of where data resides is essential for modern, efficient public services,” chimes in the Commercial Director, Government for Hitachi Solutions.

This remains an explicitly forward-thinking step for Hitachi Solutions.

One that’ll help public institutions across the UK overcome their innovation lag and ensure compliance.

The Role of Pricing Strategy in a Successful Go-To-Market Approach
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The Role of Pricing Strategy in a Successful Go-To-Market Approach

The Role of Pricing Strategy in a Successful Go-To-Market Approach

Any GTM pricing strategy should consider many molecular economic changes. But does it? Not exactly. The industry needs to learn to position price- this is how.

Let’s look at this article by HBR in 2020: Upgrading your pricing strategy to influence buying behavior.

These are the essential strategies. Frame higher prices as an upgrade or frame benefits in terms of cost or stack discounts.

While industry leaders have known this since the 90s, the public at large has just started to become aware of the subtle pricing cues the industry has set in place to make them buy, and instead of shirking away, people want to see what the tiers have to offer.

Pricing plays a huge part in decision-making, and it’s not because of the cost of the product but the trade-offs required. After all, why does anyone buy when they have a need? Cross-selling and up-selling require this, too. If the need is not as urgent—why upgrade? This is especially relevant in B2B environments where pricing influences long-term growth and positioning, much like what we discuss in B2B SaaS growth strategy frameworks.

Usually, the answer is: because the price is right (no, not the show).

The trade-off of the price matches the features. And it is this balance that organizations must achieve (btw, this is the tl:dr of the entire blog).

What Is a GTM Pricing Strategy and Why It Matters?

The pricing strategy in GTM is a deliberate choice of positioning your product/service’s cost to better reflect market needs. These market needs are defined by your potential buyers and must reflect their buying habits, something that requires alignment with your overall GTM strategy.

Why does the pricing strategy matter?

People don’t buy because the price is right, they buy because of a desire and need. While B2B buying is logical, buying decisions are based on instinct- a businessperson will trust themselves, the data will just strengthen their case.

The price operates as a data point. When buying and explaining the reason for the buy the price acts as a leverage. A leader can tell their peers “This is their price and here the ROI they can yield us.” A clear comparison that works in the suggesting leader’s favor.

Decision-makers like these are your champions, and champions are a core aspect of GTM. Building influence among them often requires a structured sales enablement strategy that arms internal advocates with data and ROI narratives.

It’s how Slack did it.

Before asking for the price, Slack lets small teams use its app. But once the user knows just how efficient communication through Slack can be- they end up as paying customers. Why? Because their price justifies it.

The pricing strategy in any GTM strategy serves a core purpose: justification. Without a cohesive marketing and positioning narrative, even the most optimized price will struggle to convert.

Why Pricing Is About Trade-Offs, Not Just Cost

The market is full of solutions that look the same. The upgrades they offer are identical, what the tool does is the same, and the distinction between them is negligible.

What remains is the story of the brand and its pricing, often contributing to making the sale.

It’s like a funnel. If the story is good, buyers check the price; if the pricing is optimal, they check the benefits and what it does for them in their context. This layered evaluation mirrors a full-funnel marketing strategy approach.

In their article, Stoa talks about trade-offs and how each decision has one. It’s a fascinating read for current and aspiring leaders. There’s a particular line that illustrates how professionals think: in trade-offs.

Of course, because neither vendors nor sellers have infinite resources. Money must be mapped, technology must be integrated into existing stacks, and all the hassle of buying a product or service, which includes the scope of failure.

It’s all a web of trade-offs on both sides.

The group of decision-makers has to think about the trade-offs involved before making a decision.

The trade-offs of the buyers that we can think of are:

Market Size

Understanding your total addressable opportunity is foundational, much like we explain when breaking down the structured GTM planning frameworks. Every organization has a limit to what it can acquire. Let’s look at the TAM of the search engine market, which is estimated to be $185.4 billion in 2024. And around ~80-95% of that market share is held by Google. (which changes depending on whether it’s desktop or mobile)

That’s a lot, but it’s still not 100% because owning any TAM is almost impossible. Even the great AI race, which should have been OpenAI’s, has many competitors.

That’s why decision-makers will think about their SOM first. Will this approach help them capture more of their market or make workflows easier so that it may happen eventually?

And importantly, can they generate enough revenue to integrate your product or service into their stack, and is it worth it?

Tech/Service Integration

Integration challenges often shape pricing tiers and packaging decisions, especially in cloud-first environments where migration and compatibility influence cost structures.

One of the most persistent problems with buying and selling any service or product is integration. And it is tough. While many organizations talk about seamless integration, there is a lot of siloed data and tools that make it impossible to do so.

There may be a lot of tools that do integrate seamlessly, but that complexity needs to be managed, and the tool becomes expensive, especially as the prices hit the premium tiers.

But also, if they do need a tool or service like yours, where will they look? At the trade-off #1 and your pricing. Then integration will become secondary. The point would be to choose the best tool based on the safety net it offers.

This is trade-off #2

User Experience

The second is whether the price justifies the user experience. Think of all the cheap alternatives to some tools- everyone uses one in their professional life at some point. These tools are alright at what you want them to do.

But the user experience is not all there. (Of course, there are some exceptions.)

Their customer service may be spotty, or if many users log in, it might start to falter. There’s a host of issues.

Or on the other spectrum, there’s a fantastic tool with everything in place, and the pricing matches that.

That’s trade-off #3.

What is the buyer’s perspective on price?

There are many trade-offs you need to consider in a GTM strategy, but pricing is one that has many strings attached.

The core question will always be: Hey, is this worth it? i.e., worth the hassle, worth the time, worth the effort, and the price decides a lot of that. The buyers want a tool or service that doesn’t add more cost, and if it does, it either returns or multiplies value.

Basic principle; often forgotten.

The price says- This isn’t bad for what it’s worth, or this is too good to pass up, and the price justifies it.

The buyers’ perspective on price will be set by the market you’re addressing. And it goes beyond competitive analysis into understanding acquisition cost structures and revenue efficiency. And it goes beyond competitive analysis. When creating or selling a service, organizations undertake complex research to address gaps.

The price must be treated the same way. It must be treated like a gap you’re trying to solve for your core buyers. And the beauty of this approach is that it helps you find the right price.

Popular Pricing Models and How They Fit into the GTM Strategy

  • Value-based pricing

    • Value based pricing is the speculation of what your product/service should be worth.
    • Through research you will identify what the price should be based on number of factors including competition, buyer-problem, market economy, and your product’s role in it.
  • Cost-plus pricing
    • Essentially, setting the price such that it covers overhead costs.
    • For example, if running your organizations costs $100, then your product/service could be priced at $150 to cover the costs. (This is a gross oversimplification.)
  • Competitive pricing
    • This is the one that even the layman knows. Essentially setting a price in response to direct competition.
    • The advantage here is that you can control the narrative and set your price at higher or lower standards than your competitors. I.e., undercutting the competition.
  • Penetrative pricing
    • This one means you undercut to build your brand. A really good strategy if you have a good product, competitive market and funding.
    • For bootstrapped organizations this is a risky move.
    • And raising prices immediately could risk alienation of the audience without clear explanation. (Marketing messages could make it apparent that the pricing is only for a limited time.)
  • Dynamic pricing and Tiers
    • Pricing that changes based on the market and their needs. Tiers fall in dynamic pricing and there is a greater chance of up-selling.
  • Premium pricing
    • Essentially creating an exclusive club through pricing alone. Take ChatGPT’s $200 tier, which outsold and outperformed the rest of the tiers because how good it was. But premium pricing requires a powerful product or service or the buyers won’t be sold on the idea.

While the pricing models are a great start, they miss three crucial elements: TAM, SAM, and SOM.

Your GTM Pricing Strategy is also about the trade-offs.

Now, let’s talk about you: the vendor.

As buyers, people naturally think about trade-offs, but do they do the same when it comes to selling? If that were so, over-promising wouldn’t be a thing.

The Role of Market Size in your GTM Pricing strategy

Misunderstanding TAM, SAM, and SOM often leads to unrealistic revenue projections, which can directly distort your broader client strategy. Essentially, a lot of businesses get their market sizes confused with TAM, forgetting the other two, which actually drive the business.

Let us explain,

So, 1000$ TAM

Maybe out of that, you take your ICP, which are SMBs in say cybersecurity, that goes to $750

And then you niche down to who you can serve, which are SMBs in cybersecurity with a specialization in Kubernetes, then your SOM is actually $450

So that means you will get the chunk of the 450$ pie, not the $1000 one. This matters a lot- because your market size will determine how you can price your product.

Whether you will have to charge a premium or make it cheap will be decided here, based on how much you need to make per customer.

This is your trade-off #1.

The Role of integration in your GTM Pricing Strategy

Integration complexity also impacts marketing budgets and operational scalability in SaaS environments.

Second is integration or complexity. SaaS products like SEMrush usually handle complexity well. And well, since most organizations today are built on the SaaS model, handling complexity is done by the servers.

But this can give rise to complexity on the buyers’ side. Integrating existing tools with yours might create silos, and someone needs to work around that. Either the vendor or the buyer has to make compromises.

And for the vendor, these compromises usually mean removing or adding features, especially knowing what the end user might go through. Often, this part is not spoken about in pricing.

It’s all about influencing the buyer, but what about setting a price that matches overhead and maintenance costs?

Or you can leverage this complexity to build tiers- think, the first tier lets your buyers handle the complexity, or tier 2, and so on, you handle it yourself. Now, there’s a reason to upgrade.

The Role of User Experience in your GTM Pricing Strategy

Okay, for this one, you won’t be able to ask for upgrades. You can’t go – you get better service because you’re paying for it.

That will ruin your pricing structure. But user experience matters, and it matters the most.

Everything hinges on how the end users feel and if the buyers see improvement in their teams’ efficiency. Even if your tool is complex and has a harder learning curve, is it learnable and teachable?

And good design requires investment, especially during GTM. Because the window to launch is usually tight. When your sales teams are displaying the tool or getting the buyer to demo it, is it intuitive enough for what it’s doing?

Investing in UX/UI and CX is costly, and the pricing must evaluate this. If it doesn’t, you may lose your customer or revenue. A business cannot run solely on ARR or MRR if it doesn’t break even. And if investors are involved, this is doubly true when pressure to perform starts mounting up.

The Role of CAC and CLV in GTM Pricing Strategy

Customer acquisition cost and lifetime value are central to pricing sustainability and must be modeled carefully to avoid revenue leakage.

Which directly leads to your customers. All trade-offs culminate here- everything your organization does yields a dollar price. From electricity to employees and the tools you use.

Your GTM pricing strategy needs to focus heavily on CAC and its CLV, for each customer, how much are you getting back if you charge $X? If the acquisition costs start mounting up and your pricing can’t catch up, that’s going to be a problem.

That means your solution cannot be so cheap that you can’t run your day-to-day. This is why many tools have premium prices and tiers, because running SaaS, AI, Cybersecurity, Data Management, SEO, etc., is not cheap. And, if it is, there is always a hidden cost that the vendors undertake.

Usually, the ones outlined above.

Pricing plays a vital role in making an organization sustainable.

While there is a lot to consider when setting a price for your product and service, it’s a task that many organizational leaders have to undertake.

Funding is good, but balancing the price helps you utilize the cash flow properly.

This is what it means to scale an organization, and that begins with GTM, not after it. A well-aligned pricing model ensures that growth, demand generation, and long-term positioning move in sync.

The Intersection of AI and Creativity
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The Intersection of AI and Creativity

The Intersection of AI and Creativity

It’s a fact that creativity has always differentiated humans from machines. But AI is changing our beliefs and casting doubts on how wide the gap truly is.

Our creative prowess is one crucial atom that has always differentiated us from machines. It’s the intuition, complex thinking, and intent behind the process that drives the difference between human content and machine content.

But the rise in AI adoption has made business leaders and marketing professionals revisit this argument, especially as AI becomes central to broader conversations around digital transformation and marketing innovation.

The ability to create was peculiar to a bunch of creatives, such as writers and designers. But today, with a couple of keystrokes and research-driven prompting, anyone can ask ChatGPT to produce a high-quality blog, design an engaging ad, and even pen down a novel.

The only succeeding question has been one of quality. Does the AI-generated blog compare to an expert with a decade of knowledge or the AI-written novel to Shakespeare’s?

However, to what extent does it hold precedence, especially over the speed and efficiency AI can afford? Why are we still stuck at using AI as a tool as an expressway to achieve business outcomes? Maybe because we are asking the wrong questions, and the existing focus needs to shift.

The market is actively investing billions into AI, giving rise to speculations on how modern tech could replace creatives. This vision is short-sighted, giving rise to even more doubts-

What is creativity without the human touch?

Let’s start the AI-creativity debate from here.

The AI-creativity debate

The market is proactively investing in the latent potential of AI, and it’s been constantly exploring the extent to which generative AI can thrive in a creative environment. And actually end up amplifying content. It was ChatGPT that prompted this thinking.

It had the market routinely questioning the disparate differences between human-created and artificially produced creativity. There are prevalent questions that have been answered:

  1. How does one nature of creativity differ from the other?
  2. How do you decide which one is worth valuing more compared to the other?
  3. Does it all boil down to valuing the labor in it?

Basically, the advent of gen AI sparked and even fueled doubts regarding the uniqueness and superiority of human-produced creative assets. So far, the advanced models have been able to create collections of different content formats- from audio to images.

And at the nexus of this wonder movement, there have also been moments of panic- does it compare to what humans are capable of? These are the two broad sentiments regarding using generative AI tools for content creation.

And business leaders and marketing professionals echo the same sentiments, particularly as brands experiment with AI-driven storytelling across demand generation ecosystems.

AI will replace human creativity: Is it a skewed perspective?

To a very significant extent, AI has become a fundamental aspect of marketing storytelling, reshaping how brands approach SaaS inbound marketing and content-led growth. And the segment that has faced the biggest hit is content writing.

Whether it’s B2C or B2B, artificial intelligence has witnessed a broad popularity. While it hasn’t yet taken over the workforce, it’s working towards it. It has sparked discussion around the fragility of human employees, how easily they’ll be replaced by this modern tech.

And it has led to a widespread belief: AI suppresses creativity. This purview is merely a speculation.

But to dig deeper into this, it’s crucial to grasp what creativity truly is and the space AI occupies amidst all of this.

A straightforward definition of creativity foregrounds the ability to create something new, practical, and surprising. An understanding that is one of the most significant hallmarks of human intelligence. So, when we’re asking whether AI does entail creative prowess, then we are basically probing if it can produce something new and surprising.

The age-old question was whether machines can generate something new. And the same has applied to AI since its introduction. The early-age programmers, Ada Lovelace and Alan Turing, dismissed any nod towards machine-generated value, one that cannot be imagined or delivered by human intelligence.

Even initial AI models, such as ChatGPT, echo this limitation. The tech’s creative output remains substantially derivative, at least for now.

Novelty and usefulness vs the element of surprise.

The truth is, creativity is messy, and its process inarguably cannot be copy-pasted. The intent, context, and judgement that creativity demands- it’s all human-centric traits. These are characteristics that truly aid humans in instilling the kind of creativity in the work they do.

So, the real question is, are large language models truly capable of creating something unique? Or are they adept at sifting through a myriad of possibilities and then creating something that appears novel? Can machines that lack the fundamentals actually be creative?

The long story short is that AI models can fundamentally do what we prompt them to do, and all of it is whatever we’re acquainted with. The thing is that LLMs are trained on massive datasets and outputs derived from probabilistic models. The responses are created from patterns they’ve learned and constantly operate on.

And even though artificial intelligence does create any ‘novel’ ideas, it does so through a specific brute-force approach. Unlike human creativity, which is powered by intent and purpose.

Does AI realize it’s being creative?

It’s a widely known concept that artificial intelligence systems aren’t creative in the traditional way. It exploits human ideas and imagination to drive anything unique, offering a sort of creative illusion.

If you roll two dice enough times, there is a significant probability that you’ll get an unusual combination at least once. This output is incidental, not purpose-driven. And that’s how the current AI models function.

Think about it: human creatives draw on complex thought processes and experiences to execute even the tiniest of ideas. It takes them days and even weeks to convert a single idea into a finished model. There’s a web of emotions, experiences, and cultural contexts that are woven to materialize a creative output.

The missing aspect is intent. And this is what is actually substantial for advertising and marketing to build genuine connections.

Do you think this sort of complexity can be tackled by learning systems that remain within a box?

Their reliance on historical data is where these models falter. Your AI models don’t know any better, at least not yet. And this stumbling block can easily give rise to legal and copyright issues- something that can topple industries such as advertising and marketing.

However, this is merely one side of the coin.

The other side doesn’t entirely cancel out AI’s potential to ideate and bring to reality any creative properties. This is something tech investors, business leaders, and Wall Street broadly believe in. And this is the vision that drives billions of dollars’ worth of investment into AI infrastructure.

AI as the strategic co-creator or a tool?

If you look closely, the crux of the conversation makes a 180-degree turn here. The conversation doesn’t surround whether ‘AI can be creative,’ but rather, to what extent it will transform creative processes.

In a recent study on Gen AI’s influence on creativity in the advertising domain, the conclusion was simple: the increasing use of Gen AI has undermined creative diversity. There’s a lack of differentiation, and each different style or format of creatives has been standardized.

With ad and marketing agencies leveraging the same prompts and data, and a strict adherence to the policy, ‘whatever worked before, could work now’- the market is facing acute uniformity. As everything becomes better, i.e., as AI helps with speed and scale, everything becomes the same. The same frameworks unify the outputs- the inflection point.

From here on, there’s one road to take- differentiating strategies to stand out.

In the same study, one of the respondents, A Head of Digital-

“I think we went through a similar thing where every Instagram grid looked the same because customers liked…this kind of imagery with this kind of text…We may end up having to go down that path with Gen AI, till you get to that inflection point…where you have to then spread back out and differentiate because everything is going to look the same if you allow it to.”

If you think about it this way, AI-generated content could become stale very rapidly. And avoiding this could demand a lot of maintenance. Someone has to take accountability and survey the end product that’s reaching the market.

AI and content creation: an assistant or a collaborator?

There are two determinants that every creative work is assessed against: novelty and usefulness (value)-

  1. Novelty measures the extent to which the output deviates from the norm and expectations.
  2. Usefulness assesses the relevance and practicality of the concept executed.

About these two components, Gen AI can work less as a job replacement and more as a collaborative tool. And the result is co-creation, a means to leverage AI in a way that augments human creativity.

One approach where its functionality has grown common is its role as a springboard for human-generated content. You can generate ideas and outlines using the AI tool, i.e., use it to provide prospective starting points that could be used to undertake different creative plotlines down the road. It’s up to the human creator to choose which path to take.

But this perspective also poses a challenge. What if gen AI roots the writer to one specific idea or starting point? The ability to establish multiple perspectives on a single situation stems from human intelligence. Because of their capability to judge. But by focusing on a single perspective, it could restrict the creator’s own thought process. And sometimes, it also conveys confirmation bias.

This way, the output would be less novel and sound similar to other content. This is where its derivative nature poses as a hindrance.

So, basically if you think about it. AI’s space in the business landscape rests on using it right, and not just using it as one pleases.

“Metacognition — thinking about your thinking — is the missing link between simply using AI and using it well.”

Each new AI model and tool brings with it another promise of enhanced storytelling and creative opportunities. This underlying value, in the form of efficiency and scale, that AI can still provide- this is how modern tech is helping human creativity evolve.

AI might not be creating the original and thought-out content that marketers and advertisers want it to. But it’s augmenting humans’ role in the creative process.

Humans are no longer mere content creators. They’re curators and editors of Gen AI content.

What AI’s perfect at is research, planning, and ideation. And at the advanced level, its capabilities of summarizing information quickly and generating multiple ideas to inspire writers and designers are in themselves a motivation. It’s a springboard, facilitating a flow of ideas, concepts, and plans to keep the blank pages filled in.

It is a strategic co-creator, at least given the capabilities of the most advanced models on the market. But only when used right.

Most businesses and teams are integrating AI models such as ChatGPT and Gemini to complete their work. But the question is, is this what AI is supposed to do- to complete your work or rather, improve it? And where is the human perspective instilled in the output? Are we at the stage where outcomes are assumed correct because they’re fabricated by a machine, all because machines can never be wrong?

This assumption is false. Humans must remain at the center of creative endeavors to retain brand authenticity and creative distinctiveness.

“This idea that you can just put something into a machine, and it bangs out an answer, and you go with it is ludicrous. The inputs you add based on your experiences- that’s the secret sauce. That is the authenticity.”

Your content creators, whether designers or writers, and SEO experts, must work in tandem with AI. A stable culture of creativity, experimentation, and inclusion is only possible when the output connects with overall brand goals and positioning.

At the nucleus of the AI-creativity debate is also an inquiry into transparency.

Both disclosure and transparency are of tremendous importance to advertisers and agencies. And principally due to the AdTech black box, there is an ensuing demand to peek behind the advertising processes, from the bidding to asset creation.

Think about the ad agencies that use AI models. The key concern here revolves around being transparent about where the models are deployed across the entire creative development process. If you’re a client paying an agency to come up with ideas using AI, won’t it beat the actual objective? The question here centers on whether outsourcing the ad agency is worth it.

And across advertising and marketing, there are always chances of copyright infringement, sensitive data disclosure, or even desensitized content based on historical data.

Making transparency between agencies and their clients imperative.

The bottom line is that the onus of accountability and responsibility lies with humans, at least in the current scenario. It’s on the brand, the humans, and the agency leveraging it.

The scrutiny and question isn’t whether AI is replacing human creativity. Instead, to truly understand AI’s space in creative strategies and content creation, the weight should be on-

Can AI balance creativity with ethical regulations? And to what extent will it be able to see this through without human interference?

Only an answer to these can truly foreground a response to the persisting question: Is AI creative?

Lead Generation For SaaS: Where are the High-Quality Leads?
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Lead Generation For SaaS: Where are the High-Quality Leads?

Lead Generation For SaaS: Where are the High-Quality Leads?

SaaS is having its big moment. Start-ups are created almost every day, they receive Series A funding, and they’re off to a great start.

But the sales? That’s another question altogether. The competition for attention is so fierce that a SaaS organization’s core buyer has at least 10-15 options to choose from. And they have already made up their mind on which one they’ll choose.

The sales conversations go nowhere, and investors become skeptical. Eventually, doors have to be closed.

The issue here is a lack of high-quality leads. And this problem has become industry-wide; big companies and small face the same drought.

Is this a marketing problem? Or a sales one?

The answer is simple: It’s organizational. No single function of an organization can be pinpointed here because, believe it or not, lead generation requires the entire organization. which is why building a structured lead generation engine becomes essential.

But it’s not happening right now, there’s too much noise and a lot of misinformation about what works. Let’s break that.

Why Lead Generation for SaaS

The SaaS market is enormous, and that’s an understatement. The size of the market is around $315.68 billion in 2025, and it’s poised to grow into $1,131.52 billion by 2032. That’s a CAGR of 20.00%.

These are gargantuan numbers. And they are undervalued, just think of this: AI is part of SaaS, and it will be valued at trillions in the coming decade.

But that means the competition will match this growth. Many start-ups, SMEs, and Enterprises will be vying for the same crown and for the same pool of buyers making targeted lead generation strategies more critical than ever. Whom will the buyers choose?

  1. It’s the organizations they know and care about.
  2. Organizations with which they have built a relationship.

And this is facilitated by lead gen.

Lead gen isn’t about data, but acquiring the buyer’s interest, building a relationship with them, and influencing their decision in your favor.

The reason SaaS treats lead generation this way is simple: subscriptions are expensive and a recurring expense at that. Businesses must be frugal with their money, especially since leaders have become aware of the VUCA. This stands for Volatile, Uncertain, Complex, and Ambiguous, which is the current state of the world. It takes trust to nurture them.

Buyers need anchors to navigate the complexity, and lead gen gives SaaS companies leverage to be that anchor. But only if the quality of leads is good.

But what are good quality leads?

Okay, good is not subjective here. Good quality leads are essentially a cluster of people – your potential buyers- that have an active interest in what you do, care about the problem you solve, and know who you are. which demands a disciplined lead qualification framework.

This is usually the prerequisite of a good lead. If some part of it is missing, these aren’t leads but people who might buy similar products/services.

A good lead is someone who can say, “Hey, yeah, I know you.”

It’s a foot in the door. But to get here, the road is quite challenging.

SaaS companies struggle with consistent, high-quality leads.

Yeah, for anyone in SaaS, this challenge is intimate. It feels as if you’re the only one struggling with leads while businesses on LinkedIn are already generating $100 Million ARR.

But why is that? It’s because marketing efforts are all spent on closing rather than converting. Performance marketing, growth hacking, and everything else are done to drive sales rather than revenue.

Hey, we get it. Investors are constantly breathing down your necks to show sales and ROI through your efforts. Being a founder, especially in SaaS, is not easy. Not even close.

But it is a trap to get this quick win. And now the industry has finally caught up, buyers prefer to be self-directed, but there are no systems in place for vendors to provide this experience for them.

Many organizations still believe being self-directed means omnichannel experiences and creating self-buy options. It’s a part, yes. However, for them, being self-directed means being in control of where their money goes and for what period of time.

The Buying Committee and the Sales Cycle.

But that is from your side. What about the buyers? There are many elements involved in the buying cycle.

  1. The buying committee- a group of 8-11 people that collectively makes the decision to buy.
  2. The internal functions of the buying organization – essentially, all the processes they need to go through to buy something. This could be Finance & Procurement, Legal, Supply Chain logistics, etc.

You have no control over these things. It is with the buyer. And it’s at this step where many lead generation strategies falter. There’s no relation-building. Especially when ignoring modern B2B lead generation strategies. And ties directly to the focus on short wins. Longer sales cycles mean more deliberation and many voices involved- how will your buyer maintain interest?

Their own processes are risk-averse and resistant to change. One of the most vital challenges of improving lead generation is for your buyers to care about what you do.

And that begins with the buyers themselves.

SaaS Lead-Generation Strategies

Let’s discuss strategies. But not some actionable framework that you will never use. But something more concrete.

In 1973, Shell’s upper management predicted the oil crisis, but they didn’t hire an oracle; all they did was present its leaders with different possible scenarios, and they did the rest.

Strategy has always been about doing unique things and anticipating likely scenarios.

1. Brand Building- Scenario

image 2

Exit Five is one of the fastest-growing B2B brands. They have built a tight-knit community around the brand, and just to make a point, here we are giving them a shoutout. That’s brand-building.

But how? The B2B community trusts Dave Gerhardt, the CEO of the brand. Just look at this post above; it has nothing to do with the brand, but there are many people appreciating him for his authenticity. And that’s how he built the brand, by making people care about what he does.

And providing value.

SaaS is moving from benefit-driven to value and trust-driven. And brands will build themselves here by

  1. Providing tangible value
  2. Aligning with a philosophy
  3. Displaying that philosophy through action

Marketing and lead generation have become relationship-based. And a great lead gen strategy means the buyers will come to you, too. Not just through your outreach.

2. The 95/5% Rule- Scenario

The second is for marketing. The answer to the long sales cycle is the 95/5% rule. Basically, it says 5% of your buyers are in-market to buy and 95% are out. But the creators of this stat advise organizations to focus on the 95%, too reinforcing long-term inbound lead generation frameworks.

To build relationships and increase the brand’s awareness. However, that’s just the visible part. The real reason is to get into the vendor’s list.

It’s an exclusive list of maybe 5-7 vendors that have been pre-decided by the buyers after careful consideration. Think about it, no one is going to hear your sales pitch and think: Right, this is what I was missing.

It takes time for buyers to understand what your SaaS product does for them and what it will do after it has been integrated.

3. Organizational Alignment- Scenario

As you can see, all scenarios point towards building relationships. And that is the crux of lead gen. While lead-generation has been misconstrued as data collection, in reality, it is a method to find the right buyer and build on that.

But how can an organization build that relationship without explaining what the tool does and how? This can be done by people in product and in engineering.

Often, marketing messages talk about sales and marketing alignment. But that’s incomplete; alignment happens between many teams first, supported by structured CRM and lead generation integration, then the message is crafted, the problem is keenly identified, and the copy is created & .

It’s this copy that the buyers connect with because it talks to them.

It’s the answer to why they should choose you. Marketing refines the message, but organizational behavior provides it in the first place.

Metrics Measuring SaaS Lead Gen Success

1. Lead-to-Customer Conversion Ratio

This one will be the most straightforward. How many leads did you get, and how many of those converted into paying customers? which ultimately determines your lead conversion rate.

That’s it. The final metric you need to keep track of.

2. Lead-to-Customer Conversion Cost

The other vital one is this. Since revenue for SaaS is monthly, the lead-to-customer conversion cost needs a lot of focus. If the costs outweigh the revenue, it’s time to look at the funnel for any friction.

3. Brand Mentions

Do people talk about your brand in the way you intend them to?

Are there conversations?

What is the number of inbound enquiries?

How much are you still spending on outreach even after you have good brand mentions and communications with the leads?

4. Time-to-Sell and Sales Velocity

What does the timeline look like? Once you have generated the leads, how long does it take them to become paying customers?

5. Real-World Example

Gong embodies all the principles we have outlined.

First, they became obsessed with their buyers- they understood what made their buyers tick. Not just their pain points, but psychological profiles too.

They then created content solely to help salespeople get better at their job, and they, the sales leaders and reps (their ICP), started to take notice of it. They hammered it home: they cared about the problem salespeople were dealing with, becoming a major player in the sales-tech world.

This built trust with their audience.

Here’s the entire case study in Devin Reed’s own words: https://blog.hubspot.com/marketing/95-5-rule-gong

So, What Now? The Right Lead Generation Partner

Lead gen isn’t easy, and that’s why agencies exist. To improve your conversion rates and increase your lead-to-sales velocity.

However, traditional agencies don’t want to understand your customer or build your brand. They treat lead generation as handing off data.

For them, leads are metrics. Not people.

It’s this chain of thinking that marketing agencies must break, and that’s what we’re trying to do at Ciente. Elevate the lead generation service process.

Multi-threading in Sales
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Multi-threading in Sales: A Timeless Principle or Just Another Strategy?

Multi-threading in Sales: A Timeless Principle or Just Another Strategy?

The complex nature of sales should not be lost to anyone. It’s not easy, even if your teams make it look that way.

Sales, by its virtues, requires an observational approach to human nature that facilitates transactional communication.

And that’s when the sales folks target only one person, but what happens when they target multiple people from the same organization?

That’s called multi-threading. And it’s an effective strategy to capture an account and build deeper relationships.

But the thing is, many top leaders and decision-makers don’t have the time or capacity to keep talking to sales reps unless there is a clear advantage. Can multi-threading solve this, or is it just another “strategy” that is more advice and less execution?

What is multi-threading, and why is it useful?

What is multi-threading in sales?

B2B marketing and sales have faced two harsh realities.

  1. The vendor list- a list of pre-decided vendors that buyers choose from. Rarely does any organization enter this list a month or two before the purchase. This process can take from a year to 6 months.
  2. The buying committee- a group of 8-11 people who make the final purchase decision.

The basic premise of multi-threading in sales is to build relationships with this group or at least try to create a web of connections inside a single account with the hopes of influencing the buying group.

At this point, multi-threading is a prerequisite as organizational power moves away from a single decision-maker to a multi-layered process.

Why is multi-threading useful in sales?

In Salesforce’s Report, 84% of business buyers expect SDRs to act as advisors. And this is no surprise, Sales has shifted to a more consultancy role anyway.

The best sellers know the value of relationships, and that’s before any of it became common marketing knowledge. Multi-threading is an extension of this practice- for the SDRs starting out in the job, speak to your head of sales or your mentor, they’ll tell you their method, and it will resemble multi-threading.

In sales and marketing terms, they don’t just talk to influencers, champions, and CXOs but to the user who will be using the end-product and to the VP of IT, all just to understand the core problem they are facing.

This is why multi-threading is useful- it gives salespeople leverage by empowering them with a deeper understanding of their account and where the entry points may lie.

Often, with all this talk of AI, organizations and even leaders forget that a salesperson’s job is to use leverage to build relationships and convey why their solution is the best one. And that begins with understanding the account in its entirety.

How can sales reps use multi-threading to close more deals?

That is the crux of the matter. How does one do it? Well, there are two ways- one is the framework way, and the other is messy, or what it’s going to look like for you when you’re on call.

Framework for creating a multi-thread strategy- Part 1

The frameworks for selling are the same across the board-

1.) Identify if the lead is valid

When pitching a prospect, you must understand the technical viability of your lead and their hierarchy. You do this with BANT, ANNUM, NEAT, MEDDIC, and whatever method you plan on using.

Identifying the lead’s place in the food chain will ensure a smoother process and set expectations. In multi-threading, if your lead is not a decision-maker, it’s fine- the point is to build relationships with the account.

2.) Identify if the problem you solve is valid for them

Okay, this step of the framework is idealistic. You want to sell the solution, and quotas must be met. When the quotas are down, this step may seem like a massive waste of time.

But the undeniable waste lies in chasing quantity. Discerning for quality yields ROI. No one is saying don’t play the numbers game, but without quality, there is no sale. Anyway, digression aside.

Once you talk to the lead, check if they are the right fit for your organization and if they require your services. And to build a relationship, this step will need you to listen to their problems instead of running off a script. Plus, in this step, you’ll realize where your leverage is.

3.) Identify the decision-makers

With Sales Navigator, this one’s easy. It practically gives you everything you need, plus intent. But when humans are involved, a bit of personal effort goes a long way. And when the intro to a decision-maker comes from their peers or direct employees, it has a greater impact on receptivity.

4.) Research and Talking The Language

Once you have connected with the decision-maker(s), you will need to personalize your pitch for the individual and their designation. While this may seem obvious, it is not.

Speaking the language doesn’t just mean knowing what the tool does; it means researching what the tool or service does for the individual.

This includes knowing how it would benefit the decision-maker and explaining how it will do that.

For example, if you sell a cybersecurity tool that safeguards data in pockets, making it easy to retrieve and access, while making the clusters secure. Since the loss of one cluster won’t affect the entire database.

The CISO may love the idea, and the CTO and CIO may agree. But the CFO and CMO might object and say this will create data silos. And then you can explain why the tool is not siloed but has a virtual copy that consolidates the data. Or something like that. And that the clusters are actually not silos but rather pockets that make searching for particular insight easier.

The pitch will change because the questions change accordingly.

5.) Maintaining the Relationships.

Here’s where a lot of multi-threading falls apart. Remember, these are leaders from the same account, and that means they are discussing the sales process. And the way sales are conducted is a reflection of the organization.

These people will have to be nurtured without feeling as if they’re transactional. That is implied, but good selling involves a bit of vulnerability with leverage. It could be something as small as a gesture of goodwill or helping them understand the market better for their context.

And for each multi-thread, you must provide a unique value. After all, any good seller acts like an account director and not an SDR. It’s almost built that way.

But beyond using email and social media to nurture, it’s the way you nurture the prospects. One really nifty way is to provide insights. Not case studies but insights into their own market, and what if the solution is yours?

Well, isn’t that just the bonus on top?

Framework for creating a multi-thread strategy- Part mess

The framework above does have a lot of mess. But there are a few things a salesperson should know, and that happens on a call.

1.) Forget the pitch.

Keep the pitchforks down, C-suites. I don’t mean slander your organization, but SDRs need to understand that the pitch exists to help them understand the buyer in the initial stages- that means the first month.

To understand what the top management wants and what the buyer needs. When you’re on-call, you must ask questions and listen to what your buyers want. Because who wants to listen to a script for the sake of selling?

Would you?

2.) Active Listening.

Apologies for making you face this one. It’s something every SDR might have heard at least once in their career. Be an active listener and get the sale.

But where this deviates is in the understanding. Active listening, the way Carl Rogers intended, was a corporate tool for leaders to understand their employees. It involves foregoing the sell for a moment.

But why? Because it presents a leverage. Talk to any human being for too long, and they give out some of their ideas and plans. And when building a professional relationship with multiple people in an account, when they know who you are, it makes for easier conversation and facilitates the exchange of knowledge.

Active listening is a tool that uncovers intent by asking the right questions, and these questions are not BANT. What can someone do to help the buyers, and do they even want the help in the first place?

But if you rush in with the questions. You’ve lost them.

3.) Comms.

There’s an industry anecdote that says if you don’t reply to an email within the hour, you lose the buyer. Now you’re going to be dealing with multiple buyers who know each other and know you’re talking to them.

How does this play out? Either you club them all in an email (not recommended, but no method, if executed correctly, is bad) or send them personalized messages from the SDR handling these decision-makers.

And here, many SDRs will have to check if the anecdote is true because they’re bound to miss some. And objections will arise. Buyers are human, and they will contact you if they have doubts.

4.) The Decision-Makers and the Sell.

There’s an intentional flaw in everything written so far. Why did anyone assume the call went forward idealistically?

What if no decision-maker spoke, or even if they did, the SDR did not know what to do. That’s a crucial problem gap, and it’s persistent. In Salesforce’s report, 74% of buyers felt the interactions were transactional.

Of course it is! But they expect consultancy.

The answer to the question is: If you don’t listen, they don’t want to buy. And the only way of increasing your chances of influencing the buyers is by showing the SDRs and CSOs care about the problem, and then also showing buyers a better way forward.

How does one do that?

By building relationships that aren’t a corporate façade.

Multi-threading in sales is the norm. Not the outlier.

Building genuinely authentic relationships has always been the best way to sell. Insurance, cars, watches, gadgets, tech, and cloud, all the best salespeople talk to multiple people.

When selling a car, a person would talk to the buyer and her husband. When selling gadgets, they speak to a person and their friend accompanying them.

When selling cloud, they speak to the CSO, CEO, CFO, and VPs.

Selling is multifaceted and messy. And that’s the way it’s always been.