Asif Ikbal Bhuiya

Digital Transformation Strategist | Global Marketing & Sales Tech Leader

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Featured illustration for blog titled 'From Search Engines to Answer Engines' showing Asif Ikbal Bhuiya with AI and search engine icons.

By Asif Ikbal Bhuiya – Global Marketing & Sales Tech Leader | Director @ RINGFEDER | B2B AI Explorer

I’ve been in digital marketing long enough to see trends come and go. But the shift we’re living through right now — from search engines to answer engines — isn’t a trend. It’s a complete change in how information works.

Search used to be a list of links. Now it’s just one answer.

And if your content isn’t that answer, you’re simply… out.

Let me show you why this matters, how I discovered the issue firsthand, and what every industrial marketer in Germany (and beyond) needs to start doing now.

🚦 I Used to Google. Now I Ask ChatGPT.

Like most marketers, I started testing generative AI tools early. I used ChatGPT, Bing Copilot, even Perplexity to see how they respond to marketing or product questions.

But what I found shocked me: Answers were partially wrong, sometimes completely off.

Why? Because our brand, RINGFEDER, serves a global audience — and different customer segments use our name in very different ways.

Our industrial couplings and trailer couplings (from a sister company) share the same brand name. Even the AI was confused — just like some of our customers. And that’s a problem.

It was the moment I realized: We need to train the AI ourselves.

That was the spark that led me to start our GEO project.

🧪 How I Found the Problem

I tested how AI answered questions about our product.

At first, it showed our distributor as the manufacturer. After several prompt variations, it finally gave the correct answer — RINGFEDER as the original source.

That inconsistency triggered a mindset shift:

“If AI can’t identify us right now, how can customers trust what it says next?”

I didn’t want our future customers, engineers, or partners to learn wrong things from a machine trained on low-quality content.

So I began optimizing for AI engines — not just Google. That’s GEO.

🧭 Search Engine vs. Answer Engine: The Core Difference

Feature Search Engine Answer Engine
Output Format List of links One synthesized response
Ranking Signal Keywords, backlinks Context, clarity, authority
Visibility SERP (position) AI answer (selected source)
Outcome User clicks and scans User reads and moves on
Marketing Strategy SEO GEO

📉 The Risk of One-Answer Systems

With Google, even if you were position 5, you got traffic.

With ChatGPT or Bing? There’s only one answer. If it’s wrong — or not yours — you’re done.

And yet, AI-generated content is flooding the internet. CVs, product reviews, guides — tons of them created in seconds.

But they lack:

That’s the gap I’m determined to fill — with correct, clear, and trusted content.

If someone asks ChatGPT about my products or company, they should get the right answer from the very beginning.

🏭 What German Industrial Brands Must Understand

Many companies are still deeply focused on SEO.

But here’s my message to German marketers:

“SEO won’t die. But it will get more complex for us — and simpler for our audience. Because SEO will become GEO.”

Your content must still rank — but now it must also be understood by machines, structured for retrieval, and wrapped in trust signals that LLMs recognize.

🛠 How You Can Start (GEO in Action)

You don’t need a big budget. Just start here:

🚨 Final Thought: GEO Won’t Retire You — But Ignoring It Might

Here’s the wake-up call:

“GEO won’t give you early retirement. But it will decide whether your digital identity survives.”

If you’re a digital leader, start now. Even with small steps. Learn by doing. Test, adapt, structure, correct.

Because the robots are already talking. It’s your job to make sure they say the right things about you.

 

Illustration showing AI tools like ChatGPT and Copilot helping with digital strategy

By Asif Ikbal Bhuiya

Let’s face it: most people still think of AI as either a futuristic robot or a flashy writing gimmick.

But for me — and for many digital leaders in real companies — AI is something more practical:
🧠 A smart co-worker
🛠 A productivity amplifier
📊 A pattern recognizer that helps ideas grow

As someone leading global digital marketing and sales technology, I don’t use AI to replace human work.
I use it to refine it, scale it, and make it smarter.

Let me show you how.

🔍 First — The Tools I Actually Use

I’ve tested dozens of platforms, but these are the ones in my real weekly workflow:

Each has its own rhythm. The trick is not choosing “one AI to rule them all.”
The trick is knowing when to reach for which one.

💼 Where AI Actually Helps in My Role

I don’t “automate everything.” I stay human — but sharper.

✅ 1. Summarizing Long Reports

Whether it’s a product spec sheet, a global market update, or a campaign analysis — I use Copilot or ChatGPT to get clear, structured summaries.
Then I shape the story based on what matters to my business audience.

✅ 2. Planning Campaign Ideas

I don’t ask AI to create campaigns.
I bring the context — and then use ChatGPT to stress-test my ideas, refine positioning, or simulate objections.

It’s like brainstorming with a very fast, always-on strategist.

✅ 3. Improving Messaging & Tone

Whether it’s internal slides, external emails, or a leadership post, I run drafts through GrammarlyGO or ChatGPT to refine structure and tone.
Sometimes I just ask, “Is this too formal?”
Turns out — AI can be a surprisingly good editor.

✅ 4. Team Enablement & Knowledge Transfer

When onboarding new team members or sharing cross-country insights, I use Notion AI to simplify complex process notes into more digestible explanations.

✅ 5. Content Planning with Confidence

I combine keyword research with ChatGPT suggestions to build outlines. Then I validate everything with real user behavior and internal data.
AI gives me speed. But strategy still needs the steering wheel.

⚖️ So… Which Tool Is Best?

Honestly? That’s like asking which is better — a screwdriver or a hammer.

Here’s what I tell others:
💡 “Try them all. Use what works. Discard what doesn’t. AI adoption is not about mastering tools — it’s about improving systems.”

🤔 Final Thought

I don’t use AI to replace thinking.
I use it to focus it.

AI helps me get to the signal faster. It clears the noise in long reports, shaky drafts, or uncertain plans.

And most importantly:
It gives me back time — so I can think bigger.

So if you’re a professional worried AI will replace you — don’t be.
Instead, use it to amplify what makes you human.

📩 Want help mapping or modernizing your stack?

You can:

📚 Want more insights like this? Explore my full blog archive for more practical strategy tips.

HubSpot Tracking URL setup showing UTM parameters for campaign tracking in data-driven marketing.

Data-driven marketing isn’t just my strategy—it’s my obsession. But let’s be honest: without tools like HubSpot’s Tracking URLs, making sense of campaign performance would feel like throwing darts in the dark.

Here’s how I’ve used Tracking URLs to turn confusion into clarity:

1️⃣ Why I Use Tracking URLs

Because guessing doesn’t cut it! HubSpot lets me add UTM parameters to links so I can finally answer, “Where are these clicks coming from?” (Spoiler: It’s usually not the email I thought would work.)

2️⃣ How I Make It Work

3️⃣ Wait… Is This GDPR-Compliant?

Good news: It is! 🎉 As long as you’re not tracking personal data (e.g., without consent), and you’re transparent about tracking practices, you’re playing by the EU’s rules. Tracking URLs themselves don’t process personal data—they just tell me which link brought traffic. (Big relief, right?)

The Result?

Better campaign ROI, fewer surprises, and more confidence in my data-driven decisions. Who knew tracking URLs could make life this much easier?

➡️ My question to you: Are you using tools like HubSpot to their full potential? Or are you still playing the guessing game? Let’s talk in the comments!

Tired of feeling like just another face in the crowd? Say hello to hyper-individualized marketing – your ticket to a personalized experience like no other, powered by the magic of AI (that’s Artificial Intelligence)!

Gone are the days of generic emails that barely catch your eye. With hyper-individualized marketing, it’s all about YOU. Here’s how it works:

Marketing with AI

Getting to Know You Better: Imagine if a marketing genie could peek into your online world, understanding not just what you buy but what makes you tick. That’s what AI does! It looks at your digital footprints – from the websites you visit to the stuff you talk about on social media – to figure out what makes you, well, you.

Mind-Reading Powers: Okay, not really, but it’s close! AI analyzes all that juicy data to predict what you might want next. It’s like having a friend who knows you so well they can finish your sentences – except this friend is a super-smart computer.

Instant Tailoring, Just for You: Ever wished a website could read your mind? With AI, it’s almost like that! Websites, emails, and even social media posts can change in real time to match what you’re interested in. It’s like having a personal shopper who knows your style perfectly.

But hey, with great AI power comes great responsibility:

Privacy First: Your data is precious, and it’s important to keep it safe. Ethical AI means being transparent about how your info is used and always putting your privacy first.

So, what’s in it for you?

Feel Seen, Feel Heard: No more being lost in the crowd! Hyper-individualized marketing makes you feel like the star of the show.
Discover New Faves: Ever had that “wow, they just get me” moment? That’s what happens when AI suggests something you didn’t even know you wanted – but turns out, you love it!
Happier Shopping: Imagine finding exactly what you need, exactly when you need it. With hyper-individualized marketing, shopping becomes a breeze.

So, are you ready to dive into the future of marketing? Let’s chat about how AI can make your online world feel tailor-made, just for you! 🚀

In the ever-evolving marketing landscape, real-life success stories speak louder than theories. Let’s journey into the world of businesses that have not just embraced data-driven marketing but have rewritten the rules of success.

Nordstrom’s Email Wizardry

Challenge: How to enhance engagement and sales through email marketing.

Solution: Nordstrom turned to data, crafting personalised emails that spoke directly to individual preferences and interests.

Result: Impressive open and click-through rates skyrocketed, directly linking personalised content and boosting sales.

Amazon’s Personalised Shopping Companion

Challenge: How to keep customers returning for more by delivering relevant product recommendations.

Solution: Amazon harnessed vast customer data, analysing individual needs and preferences to provide personalised product suggestions.

Result: The recommendation engine became instrumental, increasing sales and heightened customer satisfaction.

Netflix’s Data-Driven Viewing Pleasure

Challenge: Keeping users engaged with a streaming service in a sea of content.

Solution: Netflix analysed viewing history, genre preferences, and user behaviour to curate a personalised content experience.

Result: Users consistently return for tailored recommendations, making Netflix a streaming giant through data-driven viewer satisfaction.

Kayak’s Price Precision

Challenge: How to optimise prices in real-time for maximum revenue and customer satisfaction in the travel industry.

Solution: Kayak utilised real-time data analysis, adjusting prices dynamically based on customer search behaviour and competitor pricing.

Result: Revenue maximised, and customers found satisfaction in competitive pricing, showcasing the power of data in the travel sector.

Nike’s Personal Shopping Concierge

Challenge: How to enhance the online shopping experience for customers.

Solution: Nike delved into data, analysing purchase history, size preferences, and online behaviour to offer personalised product recommendations and exclusive offers.

Result: A customised shopping journey emerged, building a more robust customer connection and increasing brand loyalty.

Conclusion: Real Data, Real Results

In the realm of data-driven marketing, these real-world success stories illustrate the transformative power of insights. From personalised emails to dynamic pricing, the evidence is clear – businesses that leverage data survive and thrive in the competitive landscape. Let these examples inspire your data-driven journey, and witness the tangible impact on engagement, sales, and customer loyalty. The code to success lies in the data; are you ready to crack it?

In the bustling marketing world, one size doesn’t fit all. That’s where Customer Segmentation Strategies for Hyper-Targeted Marketing come into play. Whether you’re a budding marketing student or a small business owner with big dreams, understanding these strategies can unlock opportunities.

The Power of Customer Segmentation

Imagine you’re planning a surprise party. You wouldn’t invite everyone you know, right? The same principle applies to marketing. Customer segmentation is like sorting your guest list into smaller, more meaningful groups. This way, you can tailor your marketing efforts to each group’s unique tastes and preferences.

Why Should You Care?

For you, the marketing student, this is your secret weapon to stand out in a competitive field. For small business owners, it’s the key to reaching the right people without wasting time and resources on those who aren’t interested.

Navigating the Segmentation Maze

  1. Demographic Segmentation: This is like sorting by basics – age, gender, location, and more. It’s the foundation of your segmentation strategy.
  2. Behavioural Segmentation: Now we dive deeper. What do your customers do? What are their habits? Their loyalty? This helps you understand how to approach them.
  3. Psychographic Segmentation: Ever thought about what your customers like to do in their free time? Their values? This is where you dive into their minds.

Real-World Success Stories

Think about your favourite online store. They probably send you emails with products you’re interested in. That’s segmentation at work. Spotify knows what music you love; Amazon suggests items based on your browsing history – it’s all about making you feel understood.

Balancing Act: Personalization and Privacy

Hold on; ethical considerations matter. Always handle customer data responsibly and respect their privacy. Ask for permission to use their data and be transparent about your use.

Sources for Deeper Dives

“Marketing Management” by Philip Kotler and Kevin Lane Keller
“Segmentation, Targeting, and Positioning” by Jamie Murphy
Online courses on platforms like Coursera and Udemy can be valuable learning resources.

Final Thoughts

Whether you’re a marketing student looking to excel or a small business owner striving for success, mastering Customer Segmentation Strategies for Hyper-Targeted Marketing is a game-changer. You’re not just sending messages; you’re forging connections. So, dive into demographics, explore behaviours, and uncover psychographics – your key to marketing truly speaks to your audience.

Remember, segmentation isn’t just a buzzword – it’s the secret sauce to resonating with your audience. So, put on your segmentation goggles and create campaigns that hit the bullseye every time!

Sources for Further Exploration:

“Marketing Management” by Philip Kotler and Kevin Lane Keller
“Segmentation, Targeting, and Positioning” by Jamie Murphy
Online courses on platforms like Coursera and Udemy can be valuable learning resources.

 

Are you ready to take your marketing game to the next level? Imagine a world where your campaigns are so tailored to your customers that they can’t help but engage. Welcome to Predictive Analytics for Personalized Campaigns – a game-changer for aspiring marketing students and small business owners like you!

Predictive Analytics for Personalized Campaigns

Unveiling the Magic of Predictive Analytics

Predictive analytics might sound like something from a sci-fi movie, but it’s genuine and incredibly powerful. At its core, it’s all about using data to predict future behaviours and trends. In the marketing world, this means harnessing the data available to understand what your customers will likely do next. Predictive analytics gives you a crystal ball into their world, from their preferences to shopping habits.

Why Should You Care?

Personalized campaigns are your golden ticket if you’re a marketing student eager to make your mark or a small business owner looking to grow. Picture this: sending the right message to the right person at the right time. No more generic, one-size-fits-all campaigns that end up in the dreaded spam folder. With predictive analytics, you’re crafting campaigns that resonate with each individual, boosting engagement, loyalty, and – drumroll, please – sales!

Making it Simple: The Process

  1. Data Collection: Start by gathering data from various sources. This can include website visits, social media interactions, purchase history, and more. Think of this as your treasure trove of insights.
  2. Data Analysis: Now, let the magic happen. Sophisticated algorithms dive into the data, looking for patterns and connections. This is where the “predictive” part comes in. The system learns what types of customers tend to take specific actions based on their past behaviour.
  3. Predictions Galore: Once the system has learned the ropes, it can start making predictions. It might tell you that customers will likely buy a specific product in the next few weeks. With this knowledge, you can craft a campaign that speaks directly to them.
  4. Tailored Campaigns: Armed with predictions, you create campaigns that resonate. You’re not shooting in the dark anymore – you’re hitting the bullseye with messages that your customers can’t resist.

Real-World Success Stories

Remember that online store you love buying from? Chances are, they’re using predictive analytics. They know what you want before you even do it! Based on your browsing and shopping history, Amazon suggests products you’re likely to buy. That’s predictive analytics at play.

A Word on Ethics and Privacy

Hold on, though. Predictive analytics is a superhero, but even superheroes have rules. Always prioritize ethical data collection and customer privacy. Ensure you have the proper permissions to use the data you’re collecting and be transparent about how you use it.

Final Thoughts

Predictive analytics isn’t just a fancy buzzword – it’s a marketing revolution. Whether you’re a marketing student eager to learn or a small business owner striving to thrive, understanding how to harness the power of predictive analytics for personalized campaigns can catapult you to success. So dive in, explore the data, and get ready to create campaigns that your audience can’t resist!

Sources for Further Exploration:

“Predictive Analytics for Dummies” by Anasse Bari, Mohamed Chaouchi, Tommy Jung
“Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die” by Eric Siegel
“Data Science for Business” by Foster Provost and Tom Fawcett

Remember, the world of predictive analytics is exciting and constantly evolving. Embrace the journey, and watch your marketing efforts soar!

I’m excited to share the new “Search Terms With Landing Page” feature in Dynamic Search Campaigns and Ad groups. This new feature provides advertisers with a comprehensive list of all the search terms used in their campaigns and their respective headlines and landing pages. Let’s look at this feature and how it can benefit advertisers.

What is the “Search Terms With Landing Page” feature?

The “Search Terms With Landing Page” feature is a new addition to Google’s Dynamic Search Campaigns and Ad groups. It allows advertisers to access a detailed list of all the search terms that have triggered their ads, along with the headlines and landing pages used. This feature differs from the conventional “Search Term” review, which only shows the search terms that triggered the ad.

Search Terms With Landing Page Feature

Search Terms With Landing Page Feature

What are the benefits of this feature?

Using the “Search Terms With Landing Page” feature in your campaigns has several benefits. Firstly, it provides advertisers with a more comprehensive view of how their campaigns are performing. By seeing which search terms are being used and which landing pages are being triggered, advertisers can gain valuable insights into what resonates with potential customers and what needs improvement.

Secondly, this feature can help advertisers to optimize their targeting. By analyzing the search terms being used, advertisers can refine their targeting to ensure that their ads are shown to the right people at the right time. They can also adjust their ad copy and landing pages to match better the search terms being used, which can result in higher click-through rates and conversions.

Finally, the “Search Terms With Landing Page” feature can help advertisers to save time and effort. Instead of manually reviewing each search term and landing page, this feature provides a comprehensive list that can be easily analyzed and optimized.

How to use the “Search Terms With Landing Page” feature?

To use the “Search Terms With Landing Page” feature, advertisers need to set up a Dynamic Search Campaign or Ad group. Once set up, advertisers can access the feature by going to the “Search Terms” tab and selecting “Search Terms With Landing Page” from the dropdown menu.

From there, advertisers can view a list of all the search terms that have triggered their ads, along with the headlines and landing pages used. Next, advertisers can sort the list by metrics such as impressions, clicks, and conversions to identify the top-performing search terms and landing pages.

The “Search Terms With Landing Page” feature is a valuable addition to Google’s Dynamic Search Campaigns and Ad groups. It gives advertisers a more comprehensive view of their campaigns, helps optimize targeting, and saves time and effort. As a Google Ad expert, I highly recommend using this feature to gain insights into your campaigns and optimize your performance.

In today’s fast-paced digital world, marketing has evolved significantly. Gone are the days when marketers had to rely on gut instincts and best guesses to make business decisions. Today, marketers have access to more data than ever, and data-driven marketing is the way forward.

 

Data-driven marketing involves collecting, analyzing, and utilizing data to make informed decisions. It’s about using data to understand your audience better, personalize experiences, and optimize campaigns. If you’re unsure whether you’re a data-driven marketer, here are ten signs to help you identify where you stand.

  1. You Embrace Analytics

As a data-driven marketer, you don’t shy away from analytics. You love it. You actively seek ways to analyze your marketing efforts through Google Analytics, social media analytics, or any other platform. You use this data to identify what’s working and optimize your campaigns accordingly.

  1. You Focus on Metrics that Matter

As much as you love analytics, you don’t get bogged down by vanity metrics. For example, you know that likes, shares, and clicks don’t necessarily translate into conversions or revenue. So instead, you focus on the metrics that matter, such as lead generation, customer acquisition, and revenue growth.

  1. You Have a Deep Understanding of Your Audience

Data-driven marketers are obsessed with understanding their audience. You use data to learn about your target market’s demographics, interests, pain points, and buying behaviour. This knowledge helps you create targeted, personalized campaigns that resonate with your audience.

  1. You Test and Optimize

Data-driven marketers are never satisfied with the status quo. You’re constantly testing new ideas and trying to optimize your campaigns. You use A/B testing, multivariate testing, and other methods to identify what works best and then make data-driven decisions accordingly.

  1. You Use Data to Personalize Experiences

Personalization is the key to successful marketing campaigns; data-driven marketers understand this better. You use data to create personalized experiences for your audience, such as personalized emails, product recommendations, and targeted ads.

  1. You’re Constantly Learning

As a data-driven marketer, you know the digital landscape constantly changes. New technologies, platforms, and trends emerge daily, and you always learn. You attend webinars, read blogs, and keep updated on industry news.

  1. You Make Informed Decisions

Data-driven marketers don’t make decisions based on gut instincts or best guesses. Instead, you use data to make informed decisions about your marketing strategy. You rely on data to identify opportunities, set goals, and measure success.

  1. You Work Closely With the Sales

Data-driven marketers understand the importance of sales and marketing alignment. You work closely with your sales team to understand their goals and challenges and use data to help them close more deals. You also use data to identify opportunities for upselling and cross-selling.

  1. You Use Data to Drive Innovation

Data-driven marketers don’t just use data to optimize their current campaigns. You also use data to identify new opportunities for innovation. In addition, you use data to identify trends, gaps in the market, and areas where you can differentiate your brand.

  1. You Have a Culture of Data

Finally, data-driven marketing is not just about one person or one team. It’s about creating a culture of data throughout your organization. As a data-driven marketer, you encourage your colleagues to embrace data and use it to make informed decisions. You also invest in the right tools and resources to make data accessible to everyone in your organization.

In conclusion, data-driven marketing is the way forward, and the above ten signs will help you identify if you’re on the right track. Being a data-driven marketer takes effort and dedication, but the rewards are significant. By using data to drive your marketing strategy, you’ll be able to understand your audience better, create personalized experiences, and optimize your campaigns for success. So, keep honing your skills, staying curious, and pushing the boundaries of what’s possible with data-driven marketing.

In today’s digital age, being data-driven is essential for businesses to stay competitive and make informed decisions. But what exactly does it mean to be data-driven? And what are the key terms and concepts you need to know to understand digital analytics? In this article, we’ll explore the meaning of being data-driven and provide a glossary of digital analytics terms to help you get started.

What does it mean to be data-driven?

data-driven

Being data-driven means making decisions based on data and insights rather than intuition or guesswork. It involves collecting and analyzing data to understand customer behaviour, market trends, and business performance.

To be truly data-driven, businesses need to have a culture of data, where data is used to inform every aspect of decision-making, from product development and marketing to customer service and operations.

Now, let’s explore some key terms and concepts you need to know to understand digital analytics.

Digital Analytics Glossary

  1. Analytics: Collecting, measuring, and analyzing data to understand user behaviour and improve business performance.
  2. Key Performance Indicators (KPIs): Metrics that measure the performance of a business or website, such as traffic, conversions, and revenue.
  3. Data Visualization: The process of presenting data in a visual format, such as graphs, charts, or dashboards, to make it easier to understand and analyze.
  4. A/B Testing: A technique used to test two website or marketing campaign versions to see which one performs better.
  5. Conversion Rate Optimization (CRO): Optimizing a website or landing page to increase the percentage of visitors who take a desired action, such as purchasing or filling out a form.
  6. Funnel: The steps a user takes to complete a desired action, such as purchasing or signing up for a newsletter.
  7. Segmentation: The process of dividing a group of users into smaller segments based on characteristics such as age, gender, or location.
  8. Retention: The ability of a business to retain customers over time.
  9. Cohort Analysis: Analyzing a group of users who share a common characteristic, such as the date they first signed up for a product or service.
  10. Customer Lifetime Value (CLV): The total revenue a customer is expected to generate for a business throughout their lifetime.

Conclusion

Being data-driven is essential for businesses to stay competitive in today’s digital age. Companies can gain insights into customer behaviour, market trends, and business performance by collecting and analysing data. In addition, understanding key terms and concepts in digital analytics are essential to making informed decisions and optimizing business performance. Using this glossary as a guide, businesses can start on the path to becoming truly data-driven.

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