Let me begin with one of those nagging questions many marketers ask themselves. Why do consumers put products into their shopping carts and then abandon them? Well, the answer always lies in either the advertisement, the pricing of the product or the right moment to make the sale. I am afraid that in most cases such an answer is not quite correct. Let me introduce you to the Fogg Behaviour Model, which helps determine what went wrong.Product and brand teams keep coming back to it because it’s simple. In this post, I’ll keep the Fogg Behaviour Model explained in plain language and skip the academic jargon. You’ll also get a clear method you can apply this week.

A quick note on who this is for. If you run campaigns in India, you already know attention is cheap and action is expensive. People move between Instagram, WhatsApp, and YouTube all day. That’s why the Fogg Behaviour Model in marketing matters to me. It pushes you to look at what the person does next, and not only at what your ad says. I’ll cover the formula and the three parts. Then, I’ll also show how to use Fogg Behaviour Model ideas for product growth, influencer campaigns, and UGC Videos. I’ll close with a checklist you can print and stick above your desk.

1. What Is the Fogg Behaviour Model?

Now, let us start with an overview of the model first. According to the Fogg Behaviour Model, a person acts upon an action or performs an act only when three aspects coincide together. He needs some sort of motivation to perform that action. Secondly, he needs to find it feasible enough. Thirdly, someone needs to trigger him into action. That’s all. What I love about the model is its simplicity. There are usually ten boxes and five arrows in marketing models. However, this can fit into a sticky note, yet explains the failure of a lot of great marketing campaigns. Now let me explain its origins and formula and its aspects in practical marketing.

1.1 Where the model came from

BJ Fogg started the Persuasive Technology Lab at Stanford in 1998. His work looked at how software and design can change what people do. In 2009 he published a paper called “A Behavior Model for Persuasive Design.” The model took off from there. Fogg spells it Behavior on his own site, so don’t be thrown if you see both spellings. I use Behaviour here, and the meaning is identical. His original material sits at behaviormodel.org if you want the source. What I appreciate most is the tone. He never promises to make anyone do anything. He simply states what has to be true before an action can happen. That honesty is rare in marketing theory.

1.2 The Fogg Behaviour Model formula

The Fogg Behaviour Model equation looks like this: B = MAP. B is behaviour, M is motivation, A is ability, and P is prompt. Here’s Fogg’s statement in its simplest form. A behaviour takes place if there is motivation, ability, and prompt at the same time. If one of the above conditions fails to appear, then the behaviour is stopped. The idea helps you to do a quick diagnosis. When somebody doesn’t behave according to your expectations, you can easily see which letter caused problems. If motivation is low, they are not interested. If there is no ability, it’s too difficult for them.

One thing I want to point out is how the formula treats motivation. Most teams see it as the main lever. They raise budgets, add celebrity faces, and push bigger discounts. The Fogg Behaviour Model formula suggests another route. Making a task easier often works better than making people want it more. I’d go further and say it’s usually cheaper too. A shorter form costs less than a bigger ad buy. That shift changes the briefs you write for designers, copywriters, and creators. You stop asking how to make the message louder and start asking how to make the next step lighter.

1.3 Fogg Behaviour Model explained in simple words

Let me give you the plain-words version of the Fogg Behaviour Model explained. Motivation is how much a person wants to do something right now. Ability is how easy it feels at that moment, given their time, money, and energy. A prompt is whatever tells them to go ahead, such as a notification, an ad, or a friend’s message. Behaviour is the action you’re hoping for. Take online ordering. Say someone wants the product and can pay by UPI in two taps. They also get a reminder at a sensible hour. The order usually happens. Change any one of those and the odds drop. That’s the whole idea.

Motivation: how badly they want to do something right now.

Ability: how easy or difficult doing the thing feels to them right now.

Prompt: the trigger telling them to do something right now.

Behaviour: the thing you want them to do, like making a purchase, signing up, or sharing.

Make sure you always have these four terms close by whenever you plan a campaign. Use them as your checklist for each time you do it. Think of them like the checklist you run through before take-off before you even think of writing one word of copy. First, determine what behavior you want people to do. Next, think about which of the other three things is the weakest right now. It’s incredibly obvious advice but it stops you from falling into the trap of solving the wrong problem. A team that wastes weeks arguing about colors in their ads because the true problem is the slow check-out process will never succeed.

2. The Three Building Blocks Behind the Model

Each of the three parts deserves its own look. I think of them as dials on a control panel. You can turn one up, but the others still limit the result. Motivation is the dial everyone notices first. Ability is the one most teams neglect. Prompts are the ones most teams overuse. In the next sections, I’ll go through each dial and say what I’d check first in a real campaign. I’ll keep the examples practical and tied to Indian audiences. The habits and constraints here differ from what you read in most Western write-ups. Some of the advice may feel obvious. Obvious advice is often the advice people skip.

2.1 Motivation

Fogg breaks motivation into three pairs. The first is pleasure and pain. The second is hope and fear. The third is social acceptance and rejection. Every marketer touches these pairs daily, usually without naming them. A food ad that makes you hungry works on pleasure. A banner saying a sale ends tonight works on fear of missing out. A creator saying their whole circle uses a product works on acceptance. Motivation, however, is not constant either. It fluctuates throughout the day and the year as well. Motivation would go up during festive periods such as Diwali, and I would use this opportunity to make the bigger asks while keeping the rest for the other times.

Of the three motivational factors discussed above, social acceptance wins hands down in this market. Purchase decisions in India are rarely made by an individual alone. Parents have their say about phone or appliance purchases. Friends forward recommendations in WhatsApp groups. Relatives take note of what one buys. Hence, seeing others just like oneself use the product increases their desire. This is also the reason why influencers beat the brand’s professionally crafted video every single time. People believe in individuals they follow all the time. In this case, I would consider creator-generated content as a primary source of motivation. The idea of testing it only one time in a quarter would be a waste of its true potential.

2.2 Ability

Ability is how easy the action feels. Fogg lists six things that make a task hard: time, money, physical effort, mental effort, social deviance, and non-routine. Social deviance means the action feels odd to the people around you. Non-routine means it breaks an existing habit. In marketing terms, every extra form field adds mental effort. A surprise delivery fee adds a money problem. A slow page costs time. I think ability is the part to examine first, because you control it. You can’t make someone excited on demand. You can cut a five-step checkout down to two, and you can do it this week.

The numbers support this point well. The Baymard Institute has studied online checkouts for years. Its cart abandonment statistics page puts the average rate at roughly 70 percent. The reasons it lists include extra costs, forced account creation, and slow delivery. Almost none of them is about desire. Shoppers wanted the product and had already put it in the cart. Friction ended the sale. If you run an Indian D2C store, count the taps between the product page and payment. Each tap costs you a little patience from the customer, and some customers have very little to spare. Fewer taps means fewer people lost along the way.

• Time: slow pages, long forms, delayed OTPs.
• Money: hidden charges, high delivery fees, no COD option.
• Physical effort: too many taps, tiny buttons, awkward scrolling.
• Mental effort: confusing choices, unclear pricing, jargon.
• Social deviance: actions that feel risky or strange to the buyer.
• Non-routine: steps that break the customer’s usual habits.

2.3 Prompt

A prompt tells the person to act now. Fogg describes three kinds. A spark adds motivation, such as a limited-time offer. A facilitator makes the action easier, such as a pre-filled address. A signal just reminds, like a calendar alert, and works best when motivation and ability are already high. Picking the wrong kind wastes effort. A signal sent to someone who doesn’t care yet feels like spam. A spark sent to someone who’s ready feels pushy. Push notifications, emails, and WhatsApp broadcasts all count as prompts. So do creator calls to action and even a QR code inside a delivery box. I’d list every prompt your customer sees before changing any of them.

Timing decides most of what happens with prompts, and many teams ignore it. A dinner reminder at 11 am gets ignored. The same reminder at 8 pm gets tapped. Your own data will show these windows. Check when users open the app, when they browse, and when they buy. Then place prompts inside those windows. I’d also keep the volume low. Five notifications a day teach people to swipe them away unread. One well-timed message does more than five random ones. It also protects the relationship. That matters more than any single campaign when you want customers to stay for years.

3. How Fogg Behaviour Model Works in Real Life

3.1 The action line

Fogg draws a curve on a chart. Motivation sits on the vertical axis and ability on the horizontal axis. He calls the curve the action line. A point above the line means the person will likely act when prompted. A point below it means they’ll probably ignore the prompt. That’s how Fogg Behaviour Model works in practice. If a task is very easy, even low motivation can clear the line. If it’s hard, you need a lot of motivation. A one-tap reorder button gets used by almost everyone. A ten-field form only gets finished by people who are truly determined, and there aren’t many of them.

I like to use the chart as a quick exercise. Plot your key actions along the ability axis, from easiest to hardest. Signups, first purchases, reviews, and referrals make a good starting set. Then ask how much motivation each one needs. You’ll usually spot a mismatch. Teams ask for hard actions, like detailed reviews, when motivation is low. The fix is rarely a bigger discount. It’s usually a smaller ask, such as a one-tap star rating with an optional text box. Once you do this exercise, the biggest gap becomes obvious. I’d fix that single gap before touching anything else.

3.2 Motivation waves

Fogg talks about motivation waves, and I find the idea very practical. Motivation swings up and down. When it’s high, people will do harder things. When it’s low, only easy tasks work. Festive weeks, gifting seasons, and big cricket matches all push desire up for certain categories. A smart brand uses those waves to ask for bigger actions, such as pre-orders or bundle purchases. Outside the wave, the same brand asks for tiny actions, like saving a wishlist or following a page. I think this pacing is underrated. It keeps your asks in step with what people are ready to give. It also avoids the fatigue that comes from pushing too hard all year.

4. Fogg Behaviour Model in Marketing

4.1 Using the Fogg Behaviour Model for marketing funnels

To me, a funnel consists of increasingly demanding asks. The ask starts out small – watching a video, subscribing to a channel or saving a page. It is easy enough, so motivation doesn’t have to be high. Moving down, the ask increases to subscribing or trying out the product. The last thing you ask from people is money. This is a big ask so the motivation has to be high and friction low. Applying the Fogg Behaviour Model to marketing like that stops us from doing something wrong. We don’t push a purchase prompt to someone who hasn’t even heard of our brand before.

Different stages require different prompts. Someone who views a reel requires a spark – something that makes them curious. Someone browsing a product page requires facilitation – something as simple as a size chart or Cash On Delivery options. When prompts fit the stage, the funnel flows naturally and people aren’t pushed around. Instead, they are guided through the process. 

4.2 Fogg Behaviour Model examples from everyday India

UPI is my favourite among the Fogg Behaviour Model examples that you can see around you. Data from NPCI shows monthly UPI transactions crossed 10 billion in August 2023. Paying used to need cash, change, or a card swipe. UPI cut the effort down to a scan and a PIN, and shops of every size accepted it. Motivation was already there, since people like convenience. Ability jumped, and behaviour followed at huge scale. Advertising had little to do with it. For me, that’s the cleanest proof that removing friction can beat persuasion. It works even when a huge group has to change a habit.

Food delivery apps offer another set of Fogg Behaviour Model examples. Hunger supplies the motivation. Saved addresses, one-tap reorder, and quick payment supply the ability. A notification near lunch or dinner supplies the prompt. All three line up, so ordering feels almost automatic. Now compare that with a fitness app that asks you to log each meal by hand. Motivation starts high in January, but logging is tedious and the reminders feel like nagging. Usage usually fades within weeks. Both cases follow the same rule. Easy actions with timely prompts win, and hard actions with vague prompts fade, however good the product is.

4.3 A Fogg Behaviour Model framework for ads and landing pages

You can turn the Fogg Behaviour Model framework into a pre-launch checklist for every ad and landing page. For motivation, ask what feeling the creative triggers and for whom. For ability, count the steps, fields, and seconds between the ad and the goal and for prompt, check the call to action. It should be clear, visible, and placed at the moment of peak interest. Many Indian brands run beautiful ads that land on a generic homepage. The viewer has to hunt for the product, and motivation fades before ability even matters. I’d always send people straight to the exact product page instead.

• Does the first three seconds of the ad create a clear feeling?
• Does the ad link open the exact product, not the homepage?
• Does the page load fast on a mid-range phone with average data?
• Is the buy button visible without scrolling?
• Can the customer pay by UPI, card, or COD in a few taps?

A Fogg Behaviour Model marketing checklist like this takes one afternoon and a few test devices. It doesn’t need special software or a big team. I’d ask a colleague who has never seen the page to complete a purchase while you watch quietly. Take notes and say nothing. Every pause is a clue. Every wrong tap shows you where the design confuses people. Fix the biggest friction first, and only then spend on ads. You’ll often see better results without touching the creative at all. That’s a good outcome, since changing a button costs far less than reshooting a video.

5. Fogg Behaviour Model for Product Growth

5.1 Onboarding and activation

Using the Fogg Behaviour Model for product growth starts with onboarding. A new user arrives with some curiosity and very little patience. Your job is to get them to one meaningful action fast. Product people call it the activation moment. I’d cut every step that doesn’t lead there. Ask for the phone number only when you need it. Let people browse before they register. Use defaults and pre-filled fields. Add a short prompt right after install that points to the first win. Teams that treat onboarding as an ability problem usually get better activation. Teams that treat it as a motivation problem tend to struggle.

Prompts matter here too, and they shape the first impression. A short in-app tooltip works as a facilitator. A welcome message works as a spark. A reminder the next morning works as a signal. I’d keep each prompt tied to a single action. A screen that shouts five things at once confuses the user and lowers ability. Onboarding works best as a guided walk through a house. Show one door, let the person step through, and then show the next. Users who finish that first walk feel capable. Capable users come back, and each small win makes the next step feel lighter.

5.2 Retention and habit building

Growth doesn’t end at the first use. The second and third visits matter just as much. Fogg’s later work, the book Tiny Habits, came out in 2019, and you can explore the method at tinyhabits.com. It shows how to build lasting behaviour with tiny steps. The recipe is short: after an anchor moment, do a tiny behaviour, then celebrate. For a product, the anchor could be morning chai. The tiny behaviour could be opening the app to check one card. The celebration could be a small visual reward. Over time the action becomes routine. Language, meditation, and savings apps all lean on this pattern.

Streaks, progress bars, and badges work for the same reason, and most people have used one. They give a small emotional win right after the action, which is a quiet but real reward. That win lifts motivation for the next round. I’d use them with care, though. If a streak breaks and the app punishes the user, motivation crashes. Good products let people restart without shame. In India, many users share phones or deal with patchy data, so missed days are normal. Forgiving design keeps those users around. I’d build retention loops so that missing a day feels like a pause, not a failure.

5.3 Referrals and word of mouth

Referrals follow the same logic. People love to share a good deal, so motivation is rarely the issue. Effort is. If sharing means copying a code, opening a form, and reading the rules, few people bother. If sharing takes one tap, many more will do it. A WhatsApp message with a short line and a link is usually enough. India’s heavy WhatsApp usage makes this easy to use. I’d keep the share message friendly, short, and in the user’s own language where possible. Then add a reward that both sides can see clearly. Show the prompt right after a happy moment, like a smooth delivery or a five-star rating.

6. The Fogg Behaviour Model and Influencer Marketing in India

6.1 Why the influencer sits at the centre of motivation

Influencer marketing works because it raises motivation through trust and social acceptance. When a creator you follow recommends a lip balm, you don’t read it as an ad. You read it as a friend’s tip. Influencer marketing India has grown fast because internet reach has grown fast. The IAMAI and Kantar report on internet use in India estimated around 886 million active internet users in 2024. You can find the organisation at iamai.in. That’s a huge audience that watches creators daily. The influencer, whether a nano creator with 5,000 followers or a star, works as a motivation engine. People often ask how to become an influencer because of this power. I’d ask a different question: what happens after the video ends?

Famous Instagram influencers can bring a brand huge attention in a single day. Top influencers in India can reach millions with one post. Still, attention without ability goes nowhere. If the product link is buried or the landing page loads slowly, the motivation you paid for evaporates. I’d run a quick Fogg check on every influencer campaign. Does the creator spark desire? Is the path from video to purchase short? Is there a clear prompt in the caption, the story sticker, or the pinned comment? Brands that ask these questions before launch waste less budget. They also get cleaner data on which creators move people.

6.2 UGC Videos and AI UGC as friction removers

UGC Videos, short for user-generated content videos, do something special in this framework. They lower the mental effort of deciding. A real customer shows how a face serum looks after two weeks. That answers questions before the viewer asks them. Less doubt means less brain effort. Watching three honest reviews feels easier than reading a long product page. UGC also lifts social acceptance, because the person on screen looks like the viewer. Brands place UGC Videos on product pages, in ads, and in WhatsApp catalogues. I see each placement as a facilitator prompt, since it helps the buyer decide faster and with less worry.

AI UGC is the next step, and it’s moving quickly. With AI UGC, brands can produce many video variations quickly. They can test different hooks and match the tone to regional audiences. It doesn’t replace real customers. It helps teams scale what already works. A skincare brand, for example, can test a Hindi hook and a Tamil hook on the same review. Then it sees which one earns more taps. Used with care, AI UGC cuts production time and cost. That is an ability gain for the marketing team itself. I’d still keep real voices at the centre, since trust comes from them.

6.3 AI influencer marketing and smarter prompts

AI influencer marketing adds another layer. Teams running influencer marketing India wide, across many languages, gain the most from it. AI can scan creator audiences, match them to brand goals, and predict which content styles may perform. In Fogg terms, that improves the fit between motivation and message. You pick creators whose followers already care about your category instead of guessing. AI can also help time prompts, such as choosing the best hour to publish or send a reminder. The human side still matters a lot. Strategy, tone, and cultural sense come from people. The best AI influencer marketing setups combine data with human judgement, so neither side works blind.

Here’s how I’d apply all this to a festive campaign. A brand selling ethnic wear can use AI to shortlist creators across cities. A strategist then picks those who fit the brand voice. Each creator posts a story with a direct product link. A reminder goes out two days before the sale ends. Motivation comes from the creator, ability comes from the one-tap link, and the prompt comes from the reminder. All three parts are planned and tested together. That’s the real advantage of thinking in the Fogg way. Nothing is left to luck, and the team can see which part to improve next time.

6.4 Where Hobo.Video fits in

Where does a platform fit into all this? Brands often struggle to find the right creators, brief them well, track results, and fix friction. Hobo.Video is a top influencer marketing company in India that handles this end to end. With over 2.25 million creators on board, it matches campaigns to the right voices across regions and niches. The platform mixes AI with human strategy, which is how a best influencer platform should work. Brands such as Himalaya, Wipro, Symphony, Baidyanath, and the Good Glamm Group have worked with Hobo.Video. Want Fogg Behaviour Model marketing ideas to become real campaigns? A partner like this can save you months of trial and error.

7. How to Use Fogg Behaviour Model Step by Step

7.1 Pick one target behaviour

Want to know how to use Fogg Behaviour Model ideas in daily work? Start with one clear behaviour. Vague goals like “engage more” or “grow faster” won’t help you. Pick something you can see and count. Examples are “complete the first order” or “upload a profile photo.” Fogg calls this a target behaviour. I’d write it as a single sentence with a verb in it. Then decide who you’re talking about, since a first-time visitor and a loyal customer behave very differently. A fuzzy goal gives fuzzy results. A precise goal tells you where to look for friction and which prompt to build.

7.2 Audit motivation, ability, and prompt

Next, audit each part of the model. For motivation, review comments, survey answers, and search terms to see what people want. For ability, walk through your own journey on a mid-range phone with average mobile data. Many of your customers see it exactly that way. Time every step and count every tap. For prompts, list every nudge a customer receives, along with its timing and channel. Put the findings in a simple three-column sheet. Most teams find that one column is clearly weaker than the others. That’s where your next experiment should go, and it usually becomes obvious within a day.

7.3 Fix the weakest link first

Once you know the weak spot, fix only that. If motivation is low, test new hooks, creator voices, or offers. If ability is low, cut steps, simplify forms, add UPI and COD, and speed up the page and if prompts are weak, adjust the timing, wording, and channel. Fogg often advises making the behaviour easier first, and I agree with him. It tends to be the most reliable route. Changing ten things at once makes results hard to read, so change one variable per test. Give each test enough traffic and enough days to show a clear pattern. Write down every result, even the failures.

7.4 Test, measure, and repeat

Finally, measure. Track the rate at which people complete the target behaviour, and look beyond clicks or views. Compare the numbers before and after each change. Keep a simple log of what you tried and what happened. Over a few months, that log becomes your own playbook. It shows which prompts work for your audience and which friction points hurt most. It also shows which creators lift motivation best. I’d treat the Fogg Behaviour Model framework as a loop that you repeat. Each cycle makes the funnel a little smoother and the campaigns a little sharper. Those gains add up over a year.

8. Common Mistakes to Avoid

8.1 Chasing motivation alone

The most common mistake I see recommended is pouring money into motivation. Bigger discounts, louder ads, and more celebrity faces all aim at desire. Sometimes that helps. Often the customer already wants the product and is stuck on a slow page or a confusing form. Before raising the budget, check ability. Test your site on a weak network. Ask a family member to complete a purchase while you watch silently. The spots where they pause or sigh show you exactly where ability breaks. Fix those first. Your existing ad spend will work harder without an extra rupee. Sometimes the answer sits in a button, not a budget.

8.2 Misusing prompts

Another mistake is sending prompts at the wrong time or to the wrong person. A discount reminder to someone who just bought is wasteful. A cart reminder that arrives three days late feels stale. I’d split the audience by where they are in the journey. Then match the prompt type: spark, facilitator, or signal. Watch frequency too. Too many prompts teach people to ignore you. Some will switch off notifications entirely or unfollow your page. Once they do that, winning them back is much harder than never losing them. A little restraint goes a long way. Treat every message as a request for someone’s attention.

8.3 Ignoring ethics

Fogg has often said the model should be used to help people, and I agree with that fully. Dark patterns, such as hidden charges, fake countdown timers, or confusing opt-outs, may lift short-term numbers. They also erode trust. In 2023, India’s Central Consumer Protection Authority issued guidelines against dark patterns. The risk is legal now as well. Trust takes years to build and one bad experience to lose. I’d use the model to remove genuine friction and offer genuine value. When the whole truth about your product is clear, people act with confidence. They also come back without needing a nudge.

9. Measuring the Results

9.1 Metrics that match each part

Pick metrics that match each part of the model. For motivation, watch view-through rate, saves, shares, and comment sentiment. For ability, track page load time, form completion rate, and checkout drop-off at each step. Count the taps needed, too. For prompts, track click rate, open rate, and conversion within a set window after the prompt. Then link each metric back to the target behaviour. I prefer a tidy dashboard with nine numbers over a messy one with ninety. Review it every week and note which part of the model moved. That habit keeps the team honest. Then pick one number per part and watch it closely.

9.2 Reading the data without fooling yourself

Reading numbers well takes patience, since one metric rarely tells the whole truth. If motivation metrics rise and conversions stay flat, friction is the likely culprit. If ability improves and conversions rise only a little, the audience may need a stronger reason to act and if prompts get opened but nobody acts, look at the destination. Small samples can mislead, so wait for enough data. Look for patterns across weeks, not single days. Segment by city tier, device, and traffic source as well. A checkout that runs well in Mumbai may struggle on a budget phone in a smaller town. Those gaps often hide the best growth ideas.

10. Conclusion

The Fogg Behaviour Model gives you one simple lens. Behaviour happens when motivation, ability, and a prompt meet at the same moment. That lens works for a D2C founder, a growth manager, and a creator alike. Many teams now keep it as a Fogg Behaviour Model marketing playbook. Teams that apply the Fogg Behaviour Model in marketing stop guessing and start diagnosing. It tells you where a campaign broke and what to fix first. Use the Fogg Behaviour Model for product growth or for a festive influencer push. The steps stay the same. Pick a target behaviour, audit the three parts, fix the weakest one, and measure again. Over time, that routine beats guesswork.

10.1 Key takeaways

• Remember the formula: B = MAP, meaning behaviour needs motivation, ability, and a prompt together.
• Make the action easier before you try to make people want it more.
• Match the prompt type to the person: spark, facilitator, or signal.
• Time your prompts around motivation waves, such as festivals and match days.
• Diagnose any weak campaign with three questions about motivation, ability, and prompt.
• Use creator content and UGC Videos to build trust and cut doubt.
• Use AI UGC and AI influencer marketing to test faster, but keep real voices at the centre.
• Change one variable per test and keep a written log of results.

If you’re a brand, now is a good time to act. Register with Hobo.Video, a top influencer marketing company in India. Build campaigns that remove friction and drive real action. I’d call it the best influencer platform for mixing AI with human strategy. Are you a creator wondering how to become an influencer? Sign up and join over 2.25 million creators. Whichever side you’re on, the Fogg Behaviour Model gives you a clear way to plan. Pick one behaviour, remove one friction point, and launch one test this week. Small steps like these add up faster than big, vague plans.

About Hobo.Video

Hobo.Video is India’s leading AI-powered influencer marketing and UGC company. With over 2.25 million creators, it offers end-to-end campaign management designed for brand growth. The platform combines AI and human strategy for maximum ROI. To see influencer marketing India done with data and care, start here. It positions itself as a top influencer marketing company and the best influencer platform for steady, measurable results.

Services include:

• Influencer marketing
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