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Behavioral Marketing: What Are Your Customers Thinking?

Author: Ciente Editorial Team

Behavioral Marketing: What Are Your Customers Thinking?
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Behavioral Marketing: What Are Your Customers Thinking?

Behavioral Marketing: What Are Your Customers Thinking?

As value-driven experience becomes table stakes for consumers, behavioral marketing will prove to be the go-to strategy to deliver what customers truly want.

The traditional economic theory positions us, humans, as rational beings.

When it comes to making high-stakes purchases, we come forth as rational actors who operate on logic. We make choices that add to our utility. It’s the traditional economic theory- the ‘rational man hypothesis.’

Wouldn’t it be wonderful if decision-making were this neat?

It isn’t how consumers, or human beings, in general, actually function.

Human behavior is based on specific deviations from logic-driven processes. These, according to Dan Ariely, are predictable irrational cues. From a bird’s-eye view, the choices appear illogical, but if you lay them down and then study them, there are visible patterns.

These patterns won’t make sense to another party, but to consumers, every step makes perfect sense. And follows a personal linearity.

This is what behavioral marketing leans into.

What is Behavioral Marketing?

Concisely, behavioral marketing is a significant segment of marketing psychology. And a modern framework, even though this is what marketing has been truly operating on since the olden days.

In other terms, HubSpot defines behavioral marketing as

“Behavioral marketing is the method by which companies target audiences based on their behavior, interests, intentions, geolocation, and other metrics…By finely segmenting audiences based on specific behaviors or user profiles, organizations can provide relevant content and offers rather than sending general messages.”

Behavioral marketing is how your mobile phones know which product you were searching for on Google. And then gives you ads that recommend the same products. It used to be eerie- users would doubt how their phones knew precisely what they were thinking of.

But today, it’s a substantial phase of data-driven marketing.

That’s what this marketing framework is all about- the science of customer listening.

How else do you think brands promise personalization?

It’s all about applying the basics of behavioral marketing. You are spotlighting patterns and trends in how customers behave and interact with information across devices and platforms.

The Need for Behavioral Marketing

This marketing methodology taps into the gaps left by the traditional playbook. It systematically assumes several things, such as the symmetry of decision-making.

But the truth is that there’s no symmetry to consumer decision-making. The post-pandemic market is extremely disconnected from what it used to be.

The relationship between customer sentiments and spending is untethered.

Their thought patterns rarely align with their behavior patterns. The state of consumers is fragmented. Even as buyers remain vigilant about inflation and skyrocketing prices, they made very surprising trade-offs. While they trade down in some areas, they splurge in others.

Let alone B2C, even B2B marketers cannot assume a one-dimensional buying process. First and foremost, consumers aren’t privy to the brand information that marketers entail. They see what’s right before their eyes.

It’s impossible to paint an accurate picture of the bottom line with half-baked information. There are AI tools and software that can put together different data points into a clear pie chart, but is that the whole picture?

And honestly, this whole picture lacks a vital human attribute: the tendency to be impacted by transient emotions (a trait that compulsive buying is born out of).

It begs the question- is behavioral marketing only about discerning patterns from datasets?

Not quite.

Principles of Behavioral Marketing: The Science Behind

Multiple actors influence how consumers perceive and make brand choices. The choices might not be linear, but they are predictable.

Loss Aversion

Strategic decision-making depends on avoiding loss rather than making gains. According to statistics, the “torment of loss is twice as strong as any equivalent gains.”

It’s what buyers value more, especially during high-value B2B purchases- risk (loss) avoidance.

Most marketing messages delve into this, and those are the ones that actually work. Stakeholders don’t want to hear how your solution will add to their tech stack, even though the revenue impact comes later in the conversation.

What sets the primary stage is how you can solve pain points and challenges in the business. This strategy is more proactive. Companies are inherently scared of losing market share or reputation. To avoid any negative impact, they shy away from partnerships and passion projects.

Marketing can use this bias to its benefit.

Rather than spotlighting the risks, you can underline the benefits and create a sense of gain that can mitigate the buyer’s loss.

From limited-time offers to trial periods, these marketing models leverage this principle.

And the logic? Once the buyer grows used to a product, not opting for it again feels like a downgrade. When paired with a sense of scarcity (“limited”) and urgency (“only for this period”), it helps marketers ramp up the decision-making process.

Framing

How a piece of information or an offer is presented influences their decision-making processes. The entire risk aversion and potential gains conversation builds upon framing, i.e., how do you frame your messages and questions?

There is a fundamental need for a reference point around which your entire messages and brand storytelling revolve.

A perceived value can be acted upon differently, depending on how it’s framed- as a gain or a loss. This principle builds on the psychological discomfort of facing a loss as opposed to making a gain.

Think about this.

There are evidently better service providers out there, mostly in terms of monetary deals. But businesses still hesitate to make a shift. It’s about the potential loss.

Most pricing strategies follow this. The emphasis on why something works 90% of the time is better than highlighting the 10% failure rate.

Focusing on how you frame value through your marketing messages highlights the strengths of your brand over its weaknesses.

Anchoring

It’s a human tendency to believe the very first piece of information you come across. This information is an anchor or reference point that influences how we perceive the rest of the narrative.

Do you remember the iPad launch presentation?

Steve Jobs’ knack for marketing storytelling had created more buzz than the product itself.

Why?

Because Jobs plays into the consumer psychology. This marked the iPad’s price reveal as one of the most dramatic reveals of all time. The pundits had thought it to be around $1000 or more, while Steve Jobs began his presentation with the reference point of $999.

This is what the audience hooked onto. And when Jobs revealed (at the end) the actual price was to be $499, it suddenly looked attractive.

It all boiled down to the anchoring bias. The initial high price served as an anchor, making the final price look more appealing.

The same applies to some of Samsung’s popular commercials, which are basically Apple diss ads.

To remind the market that Apple isn’t the only innovative device maker, it often positions itself parallel to Apple (of course, without explicitly mentioning it!). In some of its ads, Samsung actively highlights the features Apple lacks to promote its own products with features predating its rival’s.

These principles are the fundamental blocks of behavioral marketing. And the examples are living proof that diving into the qualitative, ” the why,” works.

However, a good marketing strategy requires a structure. You cannot adopt principles and duplicate them across your messages.

Quantitative + Qualitative Framework for a Balanced Behavioral Marketing Strategy

To develop a marketing plan that actually influences your target audience, you first segregate who precisely you’re targeting. Irrespective of the marketing model, precision and contextual relevance always hold precedence.

And for your behavioral marketing to make the utmost sense, you get to the very crux-

Behavioral Segmentation.

With this function, you don’t merely segment the audience based on demographic and firmographic data, but also through their behavior patterns, interests, and preferences.

This way, you’re dividing your Total Addressable Market (TAM) into customer groups based on their previous purchases, browsing data, and choices made. It also leverages their everyday search trends and spending habits to outline insights into what exactly the buyers are searching for.

These customers have a myriad of options- the market is quite a vast arena. And with the added complexity of multiple touchpoints, personalized marketing strategies have become imperative.

Behavioral segmentation will help your team craft messages that not only resonate but are also relevant to the audience segment. This means no single message will be sent to accounts with different intent levels, from cold to hot.

This approach facilitates micro-personalization such that no buyer account feels unseen or unheard.

Behavioral Marketing Example: Amazon

An exemplary behavioral marketing example is Amazon.

Amazon leverages behavioral marketing principles to offer its users personalized product suggestions. It bases the marketing model on real-time user data as well as purchasing history.

For example, if you’re searching for a mobile phone, you’ll receive notifications regarding it. Or it’ll offer you discounted (better) deals on different phones, with the same features, the next time you visit.

From “Keep shopping” to “Pick up where you left off,” Amazon tracks behavioral cues to the bone, such as the amount of time a user spends hovering on a product and what they add to the cart.

There’s so much to behavioral marketing than merely personalized product suggestions. Dynamic ads, push notifications, loyalty programs, in-app messaging, email marketing, and retargeting are all behavioral marketing examples.

It has become a mundane modern marketing model. And savvy marketers have come to rely on it-

Vamped customer experience (personalization and precise targeting) ⇒ elevated satisfaction levels ⇒ increase in retention rates and higher conversion rates.

Behavioral marketing is marketing’s crystal ball.

Several experts and veterans believe that old marketing techniques are dead. But we say that it’s merely undergoing a much-needed evolution.

Behavioral marketing is driving this next phase.

Previously, being customer-first felt like an exception. But today, it has become the norm. With data at their fingertips, businesses have opted for and made behavioral analysis of their prospects a crucial step in their overall framework.

They grasp the vitality of a customer-first, value-driven approach. And modern marketers have made it a reality. From Facebook’s dynamic ads and Spotify’s Wrapped to Amazon and Netflix, the marketplace is undergoing a drastic revolution towards what matters to the customers.

A marketing strategy that balances both qualitative and quantitative insights.

One that bridges the gap between customer sentiments and their actual behavior.

Social media Branding
Blogs

Social Media Branding: Clearing a Misconception

Social Media Branding: Clearing a Misconception

There’s a reason your social media page is dying, and there’s no ROI from it. Your social media branding is almost non-existent, directionless, or a combination of the two.

Most brands confuse consistently posting and constant self-promotion as branding, missing the point entirely. And the ones that do it properly outshine the others, but what is the difference between these two approaches?

It isn’t just a matter of strategy but that of intent and a clear understanding of what their business does- they know what they want to say and how they say it. The other organizations are usually following a model using inauthenticity as a base and thus cannot use social media properly- they have nothing to show.

What will you show or connect on if you don’t solve a problem people are dealing with? And even if you do, if you have founders who want you to sell on social media, then that’s good luck to you because the battle has ended before it started.

And that’s where most brands find themselves, in a battle to appease everyone and no one at the same time. Branding for most teams is a performance that they can’t quite grasp.

And it is a performance because it is social media. And the answer lies in the rhythm of your own organization.

  1. What do you want to say?
  2. How do you want to portray it?

That’s easier said than done when you’re at the mercy of an algorithm and low budgets. But there is a way forward, and no, brands, it’s not TikTok.

Social Branding is building a community and influencing culture.

What is Social Media Branding?

Let’s get nerdy for a while. Above is the sigil for House Stark from George RR Martin’s Game of Thrones series. To any watcher, it is clear what the Stark banner stands for – Honor, integrity, honesty, and ferocity. The brand of the Starks- a dire wolf on snow and land is a symbol that represents their ideals and their rule over the North.

This is branding- association with ideas. While many say it’s the logo associated with the ideals, in reality, the ideals are synonymous with the logo. The ideals aggregate and become the form. In this case, the perfect form for honor, integrity, and ferocity is the dire wolf.

There is a harmony of sorts. And this is what people respond to.

So by this, we can infer that social branding is a signal that defines you. And this signal is created through the process of existing and starts to display itself quite naturally. The form and the function of the brand represent the ideals your organization or the individual stands for. And this form is created by identifying the perfect representation of the ideals.

This has been known for quite some time.

Unfortunately, marketing, in a bid to secure itself as a science, has forgotten that it is a social program and people respond to ideas first and then logic. As social creatures, we want to belong to a higher ideal- even if it is an ironic one.

But why do businesses not get social media right?

Since this is in the context of b2b, we will go with examples from brands that sell to other customers. Okay, let’s run an experiment. How many b2b brands– except OpenAI, Palantir, Anthropic, or the ones surrounded by AI hype- can you name?

Take a minute to think.

At least get to five, without googling them.

Maybe your list looks something like this:

  1. Notion
  2. Zoom
  3. Clay
  4. Shopify
  5. SemRush

Are there any overlaps? There might be at least one. Because these brands are the ones that people actually know about. That is excluding your vendors, of course. You would know your vendors. But imagine, there are so many press releases and so many social media accounts- isn’t it weird that many B2B leaders won’t be able to name many?

We bet even your employees who research and work in the trenches don’t know as much as they have been exposed to. And the reason is simple: the problems they solve are generic, the way they solve them is generic, and their approach to social media, surprisingly, is generic.

The result is a failure. You want sales from social media, but you treat your audience like a wolf hunting sheep? Constant self-promotion and no thought given to audience and community building.

Those are the reasons most businesses fail to generate high-quality leads. They are systems first and people second.

What are the b2b brands that are doing it right?

Let us explain with an example that might not date very well and is a low-hanging fruit. But hey, anything to make a point.

OpenAI released an ad campaign at the end of September 2025; it’s the organization’s first campaign. It shows no business deals or AI taking jobs (would they show it even if that is the intention?) But it does show a couple planning a dinner date, a brother and sister on a road trip, and a boy learning pull-ups.

Right now, OpenAI is in a precarious situation. Its tools are being used to automate humans away- when maybe that is not what Sam Altman wants to do (or shows that he doesn’t want to). OpenAI created this ad entirely with people and the creative agency Isle of Any.

Cementing the fact that human connection makes these tools, not the other way around. And guess what? The campaign was a monumental success. And it didn’t talk to business owners; it spoke to the people actually using AI.

The campaign is still being talked about on X and LinkedIn as this piece is being typed.

The brands that do social right aren’t just espousing values, they are infusing their creatives with what the need of the moment is: human values and less transactional interactions. But many leaders and organizations are very late to this party.

How can businesses grow their social media and improve branding?

That’s the question. And if anyone’s giving you a 10-step program to follow. Chances are, either they are fooling you or they don’t know how to do social.

Instead, if you ask an influencer what they do, they’ll give you a whole different story. And that is part of the answer: storytelling.

Business owners and their brands lack any semblance of a story. Go to any about page of a company, and all you will see is their funding rounds or some vague information about the organization. They think social media is a place where they can meet the buyers without any hassle.

But the buyers are not using social media to buy- they are using it to assess and understand the type of company you are. Your website does this, too, by the way.

So what can businesses do?

There are a few answers. But the one that sits at the core is this: It depends on the context.

Your context shapes the story you will tell. Here are some cheat codes: –

  1. Social Media is fun when your culture is.
  2. Social media branding is possible when you solve a real problem and can talk about it.
  3. Social media is a tool to propagate the knowledge your business has encountered and solved.

But what do businesses do? They undermine their own capabilities and relegate little to no creativity to social media. There is no style- something your audience wants.

But can all of this be translated to ROI?

The short answer is yes. But not in the traditional sense. See, MQLs are gone. SQLs, too. They aren’t cutting it anymore.

They don’t capture complexity or emotional nuance. The declining sales are a direct reflection of this. You’re worried that storytelling and context-driven social media marketing are just a gimmick that requires more money.

But why are you in business? Yes, revenue and the creation of jobs are noble. But so is building relationships with an audience who looks to you as increasingly inauthentic.

They aren’t going to think that what you’re doing is that you’re doing to keep your business afloat and avoid mass lay-offs. They will, with their limited perspective, believe you are hoarding money- that’s another effect of the current world economy.

But here is where your business can outpace competition.

With current B2B trends, there’s a high chance that your competition’s social media is not really good. Very few do it right- FatJoe is a strong example of B2B marketing, and it has a complete Gen-Z vibe.

But it got people talking in different circles. Different industry leaders keep commenting on FatJoe’s page because they have a knack for storytelling. Just imagine being one of these leaders and getting a call from fatjoe- even if they are skeptical, they will respond with something like: –

“Hey, yeah. I know you guys.”

They’ll be more receptive to conversations. We can bet money that fatjoe brings high-quality leads from their LinkedIn page, especially when LinkedIn pages are having a weak moment right now.

Social Media Branding is a strategy.

Michael C. Porter defines strategy as unique activities to get a desired outcome and outwit the competition [Paraphrased].

But what is the unique strategy here? Its personality. And most marketing leaders know that personality and differentiation are driving branding forward. But they are hesitant in adopting it because they aren’t quantifiable.

Historically, businesses have always been run on goodwill and communication (ethical ones, that is.) Why would today be any different? Our tools evolved for mass communication, but the needs of the people still remain the same.

They want to align with a strategic partner that helps them grow- and your social media doesn’t show that. How does something grow? Through nurturing, correct?

But if you aren’t nurturing a single component of your own business and use it for thoughtless exercises, people think that’s how you do things.

They will immediately associate you with low effort. Yes, promote your event. Promote your people. Promote your services.

But why don’t you promote your ideas and opinions? Social media branding isn’t promotion. Your buyers are doing the same thing as you; why would they be impressed by your event when theirs is so much better?

What will impress them is the content of the event. What conversations did you have? What did you learn?

What did the presence feel like?

Branding is a story. Make yours something people want to listen to.

AI will replace up to 40% of tasks, not humans, Sam Altman says
News

AI will replace up to 40% of tasks, not humans, Sam Altman says

AI will replace up to 40% of tasks, not humans, Sam Altman says

ChatGPT released one of its first marketing campaigns ever. The ad campaigns are beautiful and show how the tool enriches human life.

This is the declaration of an organization that many believe is stealing the jobs of many people.

This list starts from Software Engineers, Marketers, Writers, Designers, Researchers, Historians, and everything that requires some sort of knowledge and content production. And that list has threatened a lot of people.

Yet, the campaign has this serene feel to it, an almost harmonious quality.

But Altman was recently quoted as saying, “I can easily imagine a world where 30 to 40% of the tasks that happen in the economy today get done by AI in the not very distant future.”

That’s a very troubling thing to come from the person at the forefront of AI development. There’s no doubt that he is the face of the entire AI revolution.

He follows it up with “Think about the jobs that we did 30 years ago that may not exist at all today, or new jobs that were difficult to imagine 30 years ago that are now commonplace”.

He points out that ChatGPT-5 is intelligent than him and most people, something the users of GPT-5 may disagree with.

But he says something striking next. He says, “I believe you can never fight evolutionary biology. We are wired to care about other people and not to care about machines. We’ll be happy that these machines will be doing stuff for us, making the world richer, discovering new science, and curing diseases. But they will not be the center of the story.”

What does he mean by this? As the world fears authoritarian powers, is he positioning AI as a liberator of creativity and evolution? Yes, that is what he is saying, but does he believe it, or is this to allay the fear of the people?

The world holds its breath as the AI changes and distorts the world. All we can hope is that the creators of this technology believe it to be a force of good, not imminent destruction.

RD Technologies Discloses OristaPay, the Next-Gen Payment Infrastructure Provider
News

RD Technologies Unveils OristaPay Payments Platform – Ciente

RD Technologies Unveils OristaPay Payments Platform – Ciente

RD Technologies remains committed to advancing financial infrastructure that bridges the gap between Web3 and traditional finance.

With the winds of cross-border payments transforming, its spending is projected to hit a whopping $320 trillion by 2032.

Innovative cross-border solutions, such as Unified Payments Interface, stemmed from the demand for more transparent and swift cross-border solutions. It’s what the complexity of global money movements demands- a modernization strategy.

RD Technologies, a fintech provider, is the latest name driving innovation in the cross-border payments landscape. Its objective?

To position Hong Kong as a leading hub for digital finance.

The faster money trails have elevated access to cross-border payment means that simplify the end-to-end processes and increase delivery speed. These solutions are repairing the white gaps left behind by legacy systems.

As a part of its brand enhancement strategy, RD has announced a new cross-border brand called ‘OristaPay.’ This strategic play by the fintech provider is to differentiate the organization’s core business investments-

1. OristaPay: Cross-border payment services that comprise a fiat wallet and payment solutions, digital payment, and custody services. With RD Wallet Technologies Limited (RDWT)- a SVF licensee, this new brand will deliver secure, compliant, and innovative payment solutions to corporate clients overseas.

As RD pairs its tech innovation vision with compliance strength, this could significantly boost its market positioning.

2. RD Innotech Limited: An independently operating entity is exclusively in charge of overseeing compliance across RD’s operations. It focuses on updating and evolving the company’s regulatory framework, especially for stablecoins.

Each of these brands is a subsidiary of RD Technologies, but they’ll operate across different markets. Why?

To claw into diverse market opportunities and gain a foothold in the digital finance landscape. This is the most straightforward and clear brand strategy for RD to unlock the maximum potential of each business while remaining compliant and creating value for its clients.

Media Buying Process
Blogs

The Media Buying Process Isn’t What You Think: Why Efficiency Alone Won’t Save Your Campaigns

The Media Buying Process Isn’t What You Think: Why Efficiency Alone Won’t Save Your Campaigns

Media buying process has been painted as a neat funnel. But in reality, it’s messier and fragile than suggested. If you want resilience, here’s what actually matters.

What is the Media Buying Process?

At its simplest, media buying is the process of securing space for your message. A slot on a website, a few seconds in a podcast, a rectangle on a news page, a video that auto-plays before another video. It is where brands purchase access to attention.

But “simple” is deceptive. The textbook definition of media buying includes research, planning, negotiating, executing, and measuring. But this barely scratches the surface.

Media buying is not just logistics. It is about navigating shifting algorithms, negotiating with publishers who guard their premium inventory. And delicately balancing the trade-off between efficiency and brand safety.

This is why the media buying process can’t be thought of as a static checklist. It is more useful to think of it as an adaptive cycle where each step interacts with forces you do not control, from data privacy laws to consumer trust.

Media Planning vs Media Buying: The Twin Processes

Marketers often use “planning” and “buying” as if they were interchangeable. They are not. They are two halves of the same system, but they solve very different problems.

  • Media planning is a strategy. It is about deciding which channels and formats can best carry your story. It is the blueprint for where your message should live and why.
  • Media buying is execution. It is about securing that space in the market, negotiating costs, and ensuring delivery.

When separated, planning looks neat while buying looks tactical. But in reality, the two constantly loop into each other. A change in privacy rules can invalidate a plan. An unexpected opportunity in premium inventory can reshape strategy.

Seeing them as distinct but interdependent is key. Planning without buying is a theory. Buying without planning is a waste. Together, they form the living spine of how media works.

The Illusion of a Linear Media Buying Process

Searching for “media buying process” will recommend the same polished diagrams: define objectives, research your audience, plan channels, negotiate rates, launch, measure, and refine.

It looks like an assembly line. But if you’ve actually managed media spend, you know it rarely plays out in a straight line. The process feels more like steering air traffic in bad weather. Plans collide with competing priorities. Algorithms shift mid-campaign. Regulations change the rules overnight. Publishers and platforms protect their own margins first.

This doesn’t mean the process is broken. It means the way it is usually taught is incomplete. Media buying today is not a checklist. It is a system of moving parts that interact with regulation, human psychology, and technology. The neatness of the diagram hides the actual work.

Why the Standard Playbook Falls Short

Guides from agencies and platforms often frame media buying as a matter of mechanics. Define audience segments, pick the relevant channels, plug in creative, and optimize for the lowest CPM. They miss the friction that actually determines outcomes.

What they rarely emphasize:

  • The subtle negotiations that shape who gets priority inventory and who is left with scraps.
  • The regulatory currents that reshape targeting options mid-campaign.
  • The blind trust many teams place in programmatic dashboards, forgetting that platforms grade their own homework.
  • The obsession with surface-level efficiency hides deeper inefficiency. A cheap click does not equal a qualified buyer.

The media buying process is not only about execution speed. It’s about resilience. The winners are those who design systems that bend without breaking as the market environment shifts.

Step One: Rethinking Research

Traditional playbooks start with audience research. In theory, that means defining who you want to reach and how they behave online. But most marketers stop at what is easy to measure: demographics, intent data, and platform insights.

The flaw is that most of this data looks backward. It shows who the buyer was yesterday, not who they are becoming tomorrow. Buyers move fast. They cross devices, create anonymous identities, and increasingly resist being tracked. In B2B, decision-making rarely belongs to one person. Buying committees often involve ten or more stakeholders, each with different triggers and anxieties.

If you base your buying process on backward-looking data, you will always be half a step behind. The contrarian approach is to mix the obvious with the faint signals. Look not only at what people clicked last week but at what they are starting to talk about in niche forums, how they respond to sentiment shifts in your industry, and how early adopters behave.

That requires weaving first-party data with softer intelligence. For instance, podcast mentions or Reddit chatter are not always precise, but they are directional. They tell you where curiosity is heading. The media buying process becomes less about targeting a frozen identity and more about detecting momentum.

Step Two: Planning as Power Mapping

Most guides equate media planning with choosing channels and allocating budget. That definition is too narrow. Planning is not just tactical. It is strategic power mapping.

Ask yourself:

  • Who actually controls attention in this category? It may not be the big publishers. Sometimes it is smaller communities, niche influencers, or even customer review forums.
  • Which algorithms shape visibility? TikTok rewards creative bias. LinkedIn rewards recency. You need to know the system you are stepping into.
  • Who inside your target account can block the deal? In B2B, procurement, IT security, or legal can slow a deal by months.

It is where planning overlaps with politics. A brilliant creative on the wrong battleground burns money. Planning is about understanding the terrain before you deploy spending.

Step Three: Buying as Curation, Not Just Placement

In most textbooks, buying is the execution phase. You either negotiate directly or run programmatic ads. But in reality, buying is not just a placement decision. It is curation.

Contrarian truths:

  • Lowest CPM is rarely the best value. Cheap impressions often come from made-for-advertising sites that deliver volume but no real audience.
  • Premium placements are not only about scale. They act as a filtering mechanism. When your brand is absent from low-quality spaces, you quietly signal authority and trust.
  • Negotiation still matters. Even in the era of programmatic, private marketplaces and direct deals are the only way to secure inventory that the open exchanges will never offer.

Buying is not just about presence. It is about choosing where not to appear. Absence from the wrong places can protect brand equity as much as presence in the right places can build it.

Step Four: Execution as an Ongoing Sense Check

It’s where most campaigns fall apart. Execution looks simple on a whiteboard. Push go, watch the dashboard, optimize. But the problems creep in fast.

  • Creative fatigue sets in sooner than your testing cycle anticipates.
  • Fraudulent impressions drain budgets invisibly.
  • Cross-device continuity looks seamless in platform reports, but feels broken in real life.

Real execution requires more than watching CTR curves. It requires stepping into the buyer’s experience mid-campaign. If your retargeting follows someone into a sensitive context, you are not only wasting spend but eroding trust. Execution is not just delivery. It is a continuous sense-check against lived reality.

Step Five: Measurement Without Illusion

Measurement is where the media buying process often collapses into vanity. ROAS, CTR, CPM- metrics that look sharp on a report but do not correlate with long-term growth.

The three traps most teams fall into:

  1. Short-termism. Optimizing for immediate conversions can kill long-term brand equity.
  2. Platform bias. Dashboards are not neutral. They are designed to prove the platform’s own value.
  3. Visibility versus attention. An impression that technically “served” may never have been seen.

The better path is to measure not only what is convenient but what is consequential. Incremental lift, audience quality, and brand trust are harder to track, but they divide campaigns that build businesses from campaigns that buy clicks.

Building Resilience into the Media Buying Process

If you step back, the process is no longer just a technical workflow- it is a resilience strategy.

  • Resilience against regulation. Privacy-first design is not optional- Consent layers inside ads, zero-party data collection, and ethical use of first-party data all matter.
  • Resilience against platform volatility. Diversify across formats: display, native, DOOH, audio, AR try-ons

Relying on one channel is fragility disguised as focus.

  • Resilience against audience skepticism. Transparency matters. Label ads clearly. Selects brand-safe placements even if they cost more. Buyers notice the difference.

Treat media buying less like a funnel and more like a living system. Funnels are rigid. Systems adapt.

Why Resilience Is the New ROI

The media buying process is not dying. It is mutating. From clean linearity to adaptive loops. From pure efficiency to resilience. From chasing clicks to earning trust.

The brands that win will not simply be the ones that out-optimize CPM. They will be the ones who see media buying as infrastructure. Infrastructure designed to absorb shocks from new regulations, shifts in algorithms, and sudden swings in audience behavior.

That shift, from efficiency to resilience, is the blind spot in most guides. And it is the reason why media buying, far from being commoditized, is becoming more strategic than ever.

IT Complexity: You Can Never Solve It
Blogs

IT Complexity: You Can Never Solve It

IT Complexity: You Can Never Solve It

IT admins are always off, hurrying somewhere or the other, putting out fires. It seems that their job has moved from empowering organizations to ensuring systems stay online for efficient work.

All the while managing all compliances. Only for all of it to crash and burn after some error in some system crashes the applications the end user is working on. And then everyone panics, the DevOps team, the CI/CD team, and everyone in between starts blaming IT for not doing the job well.

That should be part of the job description – “Blame the IT guys.”

It’s a meme at this point.

However, these tech teams don’t understand that IT complexity arises because of the layers and layers of applications, services, and systems running in sync with each other.

And the solution to solve this problem is as gargantuan as the problem itself. There are many fixes that IT teams employ, but can there be a definitive one, and do leaders, beyond the CIO, get the severity of it all?

Let’s venture to search for a clear answer.

Why is the IT architecture such a mess?

No, it isn’t because the IT teams love being surrounded by wires and servers, and that’s why they build equally messy systems.

The reason behind it is that there is no clear answer to writing better code, nor can it be handled by a single system. Yes, there have been attempts at improving architecture with methods like modular monolith structures and clean architectures, but these, too, increase complexity instead of decreasing it.

The sole reason is simple: There are too many applications and API calls that muddle up the process. There’s your HR software, then there’s the CRM, then there’s the ERP, the SaaS products, the finance products, so on and so forth, and then there are the native applications.

Then there are internal productions and external tools that need access to these internal tools, and the list goes on. Imagine your IT team is not just taking care of some core business function.

They’re taking care of all of it.

And there’s another layer that goes unnoticed- the humans involved in the process.

Why does IT complexity arise?

There are many layers stacked on top of each other. Systems sending telemetry reports, the APIs calling AI systems and other software, and then there are the failures.

If a single instance crashes, maybe it’s the K8 engineer’s job, but what happens when the entire application node crashes?

That’s the problem of the software engineers, the CI/CD team, and the IT team together. Imagine so many people in one room, waiting patiently for the problem to be solved. There’s going to be tension there and the possibility of: what if we can’t solve this?

There’s the CEO breathing down your neck and the users waiting for applications to go back online. If you’re a SaaS company, these downtimes are a blow to your reputation and lead to losses.

These are the stakes, very human stakes, that give rise to complexity. And it’s an organizational problem- not just the IT department’s.

Can IT complexity be solved?

Okay, this question has no set answer, like at all. Many organizations have tried and failed. Simplification is not possible, and it doesn’t need to be.

Everyone has tried simplifying, and that created limited systems that can’t be scaled. And for start-ups and SaaS companies, well, that’s not going to fare well at all.

Growth is what makes a start-up. And SaaS must be scalable and resilient.

However, the conclusion leaders force on the IT team is to reduce complexity. There are many tools and dashboards designed for it, whether that’s scrum meetings, tools like Atlas, or initiatives that reduce human error. Maybe there’s less chaos on the field when teams collaborate to solve the problem.

Yes, that is the natural choice. However, there is something deeper that operates within this system. And it cannot be solved for.

It is an immutable law of all systems: entropy.

IT complexity can be managed, not solved.

This piece has actually turned into a venture. While researching, we found many disparate solutions. Some pieces suggest using a tool or using a single vendor, but won’t these create newer complexities?

Most leaders take a brute force approach to solving complexity- let the IT guy do it. And while your CIO does cut costs for you and reduce everything universally possible, they will hit limits that aren’t physically scalable.

Yet, leaders want growth. Growth at the price of what exactly?

The answer is clear: operational efficiency.

Companies eliminate operational efficiency to save money and customer uptime, ending up in a loop where this exact thing starts affecting their business negatively. Let’s talk about Larry Tesler’s law, called Tesler’s law (go figure!)

In it, he posits, every application has an inherent complexity that cannot be removed or hidden. Instead, it must be dealt with either in product development or in user interaction.

The simplest example of this is the GUI. Organizations manage complexity while users click buttons and levers. The same is happening to your servers, and while you can use managed services, which is actually the easier option, it moves the complexity to another plate. And then they have to manage complexity.

But the point is to make leaders aware of the variables involved and what they need to do.

So we’ve got down to the awareness of it all. Eliminating complexity won’t actually make your systems smarter; computing gets rigid. It cannot be scaled.

What role does entropy play in IT complexity?

Every system experiences entropy. It reaches a state of equilibrium, i.e., from structure to non-structure, and this non-structure is essential. Balanced entropy in computing actually makes the systems efficient.

But, as applications are stacked, the entropy reaches a tipping point where the information devolves into disorder or the rate of disorder begins to increase. For example, here’s a simulation we ran.

Imagine you have 73 servers, which are 98% resilient, and then you have a 74th server with 95% resilience. The probability that at least one node in the server fails is 78%, which is the baseline. Now, imagine what happens when applications and nodes fail in succession?

It’s chaos.

And that’s why there are days when your systems crash, servers can’t be accessed, or end users experience downtime. And there’s at least one day when this happens.

Remember CrowdStrike? The cascading effect is entropy at work. Since all systems are interdependent, one failure could lead to the next. And it does this to achieve equilibrium.

In short, your systems fail because it’s the path of least resistance.

So what can help you here? As leaders, you need something that has existed before was even a thing.

It’s called Chaos Engineering.

And your CTOs, CIOs, and even Jr. Engineers, probably and hopefully, know about it.

Chaos Engineering- Pioneered by Netflix.

What is the most server-intensive task in the world? AI data centers are obviously number one. And number 2 has to be Netflix (opinion alert).

They completely changed how businesses move to the cloud. Every organization wants to create a resilient system, but how exactly?

This is the answer. It has the makings of a great strategy.

  1. It’s context-based.
  2. It asks questions that are relevant to your problem
  3. It simulates and gives probabilities of failures and weak points.
  4. It has a cool name.

So what does it do? Essentially, engineers at Netflix understood that their servers bring in a lot of people. And failure is imminent – it’s not unavoidable but imminent. A matter of time before something crashes.

What happens when 1.5 million or 10 million people log in to watch Stranger Things? Of course, Netflix being Netflix, that won’t crash them because they will be prepared. How? Using their Simian Army.

No, it’s not like the monkeys Lex Luthor uses in the pocket universe in Superman. But, a method of anticipating failure points and preparing for them. They developed this by imagining a monkey with a wrench wrecking havoc on their systems.

With this, they found vulnerabilities that they could never have anticipated by shutting down instances and entire servers to see what would break and what would remain functional. They knew that IT complexity wouldn’t be a clean solution.

Netflix knew they had to break things (virtually, of course) to see what was affected and what was not. That was 14 years ago in 2011.

Now, Kubernetes, Grafana, and other tools make it easier to handle failures, but the complexity hasn’t gone anywhere. Instead, chaos engineering might become a focal point of future software development.

As AI builds code or users delve into AI-assisted coding, what would matter the most? Identifying failure points as complexity arises.

In short, a person who can anticipate failure, create systems for it, and manage complexity. Which of course will require clear documentation- yes, documentation that cannot be replicated by AI but by someone who sees clear patterns and observes systems as they become more complex.

Maybe, the future of development is not less complexity but more complexity stuffed into efficient packets- that’s worth exploring.