by Christina | Apr 3, 2025 | 2025, Business Trends
In today’s economic climate, losing a customer isn’t just disappointing—it’s potentially devastating. Yet many businesses miss the early warning signals until it’s too late.
I’m experiencing this firsthand with one of our vendors right now. The relationship is deteriorating, and I can see exactly where things went wrong. Don’t let this happen to your business. Here are the critical warning signs to recognize and address immediately:
1. Service Deterioration
When service quality stumbles at the start and never recovers—or worse, begins strong but steadily declines—customers notice immediately. This often stems from internal turnover or stretched resources, but regardless of the cause, clients can sense when they’re no longer a priority. Remember: consistency is as important as quality.
2. Communication Breakdown
Poor communication compounds service issues and accelerates relationship decline. Worst of all is attempting to cover problems with transparent excuses—this damages trust far more than the original issue. The solution is straightforward but crucial: honest, proactive communication can salvage even troubled relationships.
3. Eroding Trust
If your customer begins questioning your expertise or experience, you’re facing a five-alarm fire. Once trust evaporates, recovery becomes exponentially more difficult. This warning sign demands immediate intervention—schedule a candid conversation about expectations and reset the relationship before it’s unsalvageable.
4. Subpar Deliverables
Sometimes the sales team sets impossible expectations, creating a delivery gap from day one. Other times, businesses overreach beyond their core competencies. Either way, consistently disappointing deliverables will end relationships. Focus on excelling at what you do best rather than attempting to be everything to everyone.
5. The Toxic Team Member
One underperforming team member can poison an entire customer relationship. Don’t retain problematic employees simply to fill a position—they consume disproportionate management resources while actively damaging customer relationships. Make the difficult staffing decisions before they cost you valuable clients.
6. The Preemptive Reset
Sometimes the boldest move is acknowledging when you can’t meet expectations. Proactively addressing shortcomings—even suggesting a pause in the relationship—demonstrates integrity and preserves future possibilities. A temporary revenue hit is preferable to a permanently damaged reputation.
The Path Forward
Customers don’t make switching decisions lightly. When a vendor is deeply integrated into operations or fulfills a critical function, transition costs are substantial. This reality often creates a window for relationship recovery—but only if you recognize the warning signs and act decisively.
Use this opportunity to genuinely improve your service delivery. Not only might you save the relationship, but you’ll also remove the constant weight of knowing you’re underserving a client—a burden no business owner should carry.
by William Walsh | Jul 15, 2024 | 2024
As previously published on 7/11/24 in MarTech
Did you know that you have your own intent data, you don’t need to buy it. If you are executing campaigns, especially in existing accounts you have data that goes much deeper than what you could buy.
You just know where, and how, to look for it. Once you find it you will realize that what has been sold, or said, to you about “signals” isn’t exactly true.
As marketers, we’ve been told that there is a connection between a “signal” of a prospect seeking information with their interest in your company or product. That a response to an offer made could imply they’re “in the market to buy”
This is how Zoominfo describes intent data based on signal strength.
- “Derived intent signals are a mix of first-party and third-party signals. These offer insights into behaviors that indicate interest in a company, such as ad engagement, web activity, topic engagement, and technology use.”
As a result, we have a tendency to think of this as a MQL. But this is where things break from reality. Again from ZoomInfo:
- “Identify interest: Purchase-intent signals help identify which companies are actively researching your solution before they fill out a form on your site or engage with your sales and marketing teams.”
This is simply not true, it’s an assumption. Let me break it down, unless you understand a buyer’s personality, which would give you real insight into their behaviors and motivations, and you are able to observe this over time, you can not assume that they are “actively searching” for what you are offering because they have ‘purchase intent.”
We have found only a small percent (5-10%) of cases where this is true, and we have evaluated engagement and intent data across 7 industries and thousands of interactions. When you look at your own data you will find the same thing.
Given the fact that 5% of your targeted audience is in a buying cycle at any one time this would make sense. But what is more interesting is what is in the 95% of data that you aren’t analyzing or buying.
Here’s what you need to know about to analyzing your own engagement data
First, pull data from your sales and marketing systems at the account level. We’re often so busy executing we rarely have time to look at what has happened in the past. You’ll want to pull 12 to 18 months of engagement data based on the length of the sales cycle.
Pull data on 10 accounts to start. They could be the 10 biggest or most important (based on pipeline value) accounts. Here’s what you’ll want to look for in the data.
- Engagement over time – this is an important metric because it’s a measure of mindshare you have with a buyer/contact. Look for how they have engaged with your outreach over the past 12 to 18 months. Is it a “burst,” for example, a C-level engages multiple times in a month or is it “consistent” – a couple of engagements over a longer period of time.
- Engagement time – how much time did they spend with whatever was offered. Was it millisecond or seconds? This will help you understand their level of engagement. Are they glancing at what was sent or did they dig deeper?
- Engagement frequency – did they hit one thing multiple times in one day, and over a period of time? This may be an indicator of them forwarding information to others. And it gives you insight into who might be the “router” of information inside of the account.
- Engagement offer – what are they engaging with, e.g. what offer or outreach. Are they looking at webinar invites, new case studies, reading the newsletter, etc. Having 10 accounts will give you real insight into what content really matters.
This insight will help you understand if the audience is interested in your brand, solution, or just what was offered.
Most times, it will be just the offer. But that’s a great insight because it allows you to narrow down your activities to the things that really matter to your audience. What content offers really do is they open a window for a salesperson to be viewed as valuable. It doesn’t tell you if the target is in a buying window or in a certain part of the buyer’s journey, unfortunately.
Giving the sales organization insight into how, and what, audiences are engaging with enables them to focus on starting a relationship. Through a better understanding of why people are doing what they are doing, it gets to their real motivations. The signal becomes insight.
For example, did they look at your upcoming webinar invite or user conference? How many times did they look at it? How many emails related to those events did they open? Did they attend the event? If they didn’t, you now know they were interested.
This creates an opportunity for the salesperson to offer an on demand version of the webinar or maybe a free pass to next year’s event. They’re building a relationship based on interest, not jumping to selling a solution where they have shown no real interest in pursuing.
And that is what is in your 95% of the engagement data that doesn’t get analyzed. It tells sales who to spend their time with, and how to start a relationship, that one day could become a new customer.
by William Walsh | Jul 1, 2024 | 2024
By Scott Gillum
Estimated read time: 3 Minutes
Want to take your ICP’s to the next level? Try using personality based marketing to understand corporate cultures.
Here’s why. Above are 2 SaaS companies in the martech industry. Our client is selling to the same buyer in each company. But the company situations are vastly different.
The first company is growing aggressively and has a corporate culture that is full of “Dominate” personalities.
The second company is under attack and has lost significant revenue and market share during the last two years. The corporate culture is skeptical, given the prevalence of “Consciences” personalities.
So what does all this mean?
First, it impacts the positioning of the value of your product.
Second, it helps you identify the right set of the sales and marketing assets.
In company 1, you position the value of the offering to help scale growth.
You communicate that through case studies with ROIs. Given their “dominant” culture, they are heads down operators so use relevant case studies that align, as closely as possible, to their situation.
In company 2, you position the value of the product on what it can do to drive efficiency.
This is a company fighting for its survival. It needs ideas on how to improve operations. As a result, use cases showing potential cost savings (business cases) are most important.
And given the culture, use data and research to support the use/business cases which is essential for building credibility in selling to an organization like this.
Before you even speak to a buyer you can understand the environment in which they operate. It allows you to create a connection — optimism for company 1, empathy in company 2.
ICP’s are not just an acronym, they’re people. Decisions are influenced by emotions. Motivations cause decisions, and personality dictates both.
The more you understand this the higher the likelihood of getting engagement, interest, and a decision. It’s a 1, 2 punch.
by William Walsh | Jul 11, 2023 | 2023
As previously published on 6/28/23 in MarTech
By Scott Gillum
Estimated read time: 5 Minutes
What if they are wrong?
When responding to questions about AI replacing humans in certain roles, most ‘experts’ claim that AI will replace some jobs, but will be a much more valuable tool for augmenting human intelligence and ability.
In all of the hype associated with this latest technology wave, an important trend is occurring across industries that could significantly change the impact of AI – the retirement of the knowledge worker.
We need to look no further than the last wave of intelligent technology – the “internet of things” (IoT) to see the impact.
The term ‘Internet of Things’ was coined in 1999 by computer scientist, Kevin Ashton. While working at Procter & Gamble, Ashton proposed putting radio-frequency identification (RFID) chips on products to track them through a supply chain.
“Machines talking to machines” started rolling out in early/ mid 2010 making their way into manufacturing, precision agriculture, complex information networks, and for consumers in a new wave of wearables.
Now, having about a decade of experience of how IoT has impacted certain industries and markets, perhaps it can give us some interesting insights on the future of AI.
In 2010, Cisco launched the “Tomorrow Starts Here” IoT campaign at the time when communication networks were transitioning from hardware “stacks” to software development networks (SDN).
The change meant that in order for carriers to expand their bandwidth, they no longer needed to “rip and replace ” hardware. They only needed to upgrade the software. This transition began the era of machines monitoring their performance and communicating with each other, with the promise of one day producing self healing networks.
Over this same period, network engineers who ushered in the transition from an analog to digital began retiring. These experienced knowledge workers are often being replaced by technicians who understand the monitoring tools, but not necessarily, how the network works.
Over the last dozen years networks have grown in complexity to include cellular, and the number of connections has grown exponentially. To help manage this complexity, numerous monitoring tools have been developed and implemented.
The people on the other end reading the alerts see the obvious, but have a difficult time interpreting the issue, or what to prioritize. The reason is, the tool knows there is an issue but is not smart enough yet to know how to fix it or if it will take care of itself. Technicians end up chasing “ghost tickets,” alerts that have resolved themselves, resulting in lost productivity.
The same thing is repeating itself in marketing today. As one CMO told me; “I can find people who know the technologies all day long, but what I can’t find is someone who thinks strategically. Ask a marketing manager to set up the tools and run a campaign and they have no problem, but ask them to write a compelling value proposition or offer for the campaign, and they will struggle.”
It’s easy to get sucked into the tools. AI generators are really intriguing and can do some amazing things. But based on what we have seen, the tools are not smart enough to fully deliver on their promise…yet.
Here’s the warning from IoT – as tools become more knowledgeable, the workforce operating them is becoming less. It is leaving a knowledge gap. As that knowledge is transferred from worker to machine, we need to ask ourselves what we’ll be left with. Will there be enough experience and expertise in our workers to know if what comes out of the machine is accurate, factitious, or even dangerous.
In a recent WSJ article, Melissa Beebe, an oncology nurse, commented on how she relies on her observation skills to make life-or-death decisions. When an alert said her patient in the oncology unit of UC Davis Medical Center had sepsis, she was sure the AI tool monitoring the patient was wrong.
“I’ve been working with cancer patients for 15 years so I know a septic patient when I see one,” she said. “I knew this patient wasn’t septic.”
The alert correlates elevated white blood cell count with septic infection. It didn’t take into account that this particular patient had leukemia, which can cause similar blood counts. The algorithm, which was based on artificial intelligence, triggers the alert when it detects patterns that match previous patients with sepsis.
Unfortunately, hospital rules require nurses to follow protocols when a patient is flagged for sepsis. Beebe could override the AI model, if she gets doctor approval, but faces disciplinary action if she’s wrong. It’s easy to see the danger of removing human intelligence in this case, it also illustrates the risk associated with over relying on artificial intelligence.
AI will free us from low value tasks, and that is a good thing, but we need to redistribute that time to better developing our people, and our teams. The greatest benefit from these game changing technologies in the business to business environment will be realized when we combine equal amounts of human intelligence with machine intelligence.
by William Walsh | Feb 21, 2023 | 2023
By Scott Gillum
Estimated read time: 5 Minutes
Imagine adding one of the world’s greatest artists to your creative team. Or, how about saving time and money on creative brainstorming by starting with a first draft to inspire the team. How about creating dozens of creative concepts in the same time it currently takes to develop a handful.
Intrigued? This is the promise of AI creative engines for B2B marketing. And with that possibility, could it also help make B2B marketing as sexy and exciting as B2C advertising?
The big story of this year will be the widespread adoption of AI creative tools. Chat GPT is just the beginning. Expect to see agencies widely embrace AI for all types of creative – not just content. Open AI’s CEO, Sam Atlman, sees the “greatest application of AI for creative use,” not in replacing blue collar jobs as many had predicted.
After experimenting with AI tools for the last couple of months, you may be interested to know that I totally agree with Sam’s statement. In fact, the image used for this blog was created using Jasper’s AI image generator.
I selected Salvador Dali as my inspiration, acrylic paint as the style, the context of creating an exciting and bold prediction for the future, out pops the image you see. There were almost endless options of possible combinations that could be used from style to mood, and everything in between.
Rather than these tools being utilized to replace people, they have the potential to be incredibly useful tool sets that in a sense, may serve as an “inspiration engine” for creatives. The potential for increase in productivity is huge!
In fact, think of the possibility of having a famous artist inspire the creative team. Instead of replacing people, you’re gaining access to an incredible talent pool that would otherwise be impossible. Talk about shaking up the world of B2B that has a tendency to lean on technical language and images of products.
The creative process is nothing if not iterative. Imagine how fast the team can play around with concepts by using AI content generators to create first, second, and third drafts that are then edited and approved by a human as final copy.
Consider the time saved by having a designer build the exact image they want, rather than scanning Getty Images for hours on end. Oftentimes, just getting started creates a delay. Working off an AI generated first draft could accelerate the process – at least, that’s the hope.
Now the warning. It is very easy to write long form and short form copy using AI tools, especially for digital ads, blog posts and emails. For B2B marketers, this could mean that there is an easily accessible cornucopia of content to blast out to prospects. Please use these tools judiciously.
The assumption that more content equals more engagement is incorrect. Relevant content is closer, but it still requires insight and strategic thinking, which you will not find in AI tools. The new generation of AI generators is very powerful, in particular, with the coming release of GPT-4 and the advancements made in language modeling.
The tools still require time to learn and understand how to best utilize their power and get the output you desire. There is, however, a learning curve – it is not as simple as input and output. There are numerous variables that need to be refined or manipulated by humans in order to achieve a quality output. The expression of “crap in, crap out” still holds true.
Agencies and companies who carefully consider experimenting with these new tools will now be better off in the long run as technology continues to advance. And here’s another warning based on our learning in young marketing using technologies, they are not the goal.
It’s not enough to only know how to use the tool, you still need to think creatively. AI generators can be great tools to aid the creative process, don’t let them become the process.
They don’t become a threat for replacing humans if you understand how to use them properly. And no, I didn’t use an AI content engine to write this blog…or did I?
