Jan 27 2025
How YouTube’s Recommendation System Works In 2025 via @sejournal, @MattGSouthern

In a recent video interview, YouTube Liaison René Ritchie spoke with Todd Beaupré, YouTube’s Senior Director of Growth & Discovery, to discuss the platform’s recommendation system functions and what creators can expect this year.

Their discussion revealed how time of day, device type, viewer satisfaction, and the advent of large language models (LLMs) are reshaping YouTube’s algorithms.

Here’s what you need to know about YouTube’s recommendation system and how it works.

Personalized Recommendations

One of the central themes of the interview is YouTube’s focus on matching content to individual viewer preferences.

According to Beaupré:

“Often times creators will say hey, uh the recommendation system is pushing out my video to people or why isn’t it pushing out my video yes they they may ask that and the way the work it works is it… isn’t so much about pushing it out as much as it’s pulling…”

He goes on to explain that YouTube’s home feed prioritizes content based on what each viewer is most likely to enjoy at any given moment:

“When you open the homepage, YouTube is going to say hey Rene is here, we need to give Rene the best content that is going to make Rene happy today.”

Metrics & Satisfaction

While click-through rate (CTR) and watch time remain important, YouTube’s system also accounts for user satisfaction gleaned through direct surveys and other feedback signals.

Beaupré notes:

“We introduced this concept of satisfaction… we’re trying to understand not just about the viewer’s behavior and what they do, but how do they feel about the time they’re spending.”

He explains YouTube’s goal is to cultivate long-term viewer satisfaction:

“…we look at things like likes, dislikes, these survey responses… we have a variety of different signals to get at this satisfaction… we want to build a relationship with our audience just as creators want to do with their fans.”

Evergreen & Trending Content

YouTube’s algorithms can identify older videos that become relevant again due to trending topics, viral moments, or nostalgic interests.

Beaupré cites the system’s ability to pivot:

“…maybe like right now there’s a video that that reaches a certain audience but then like in six months… that makes this video relevant again… if it’s relevant and maybe to a different audience than enjoyed it the first time.”

Context: Time, Device, & Viewer Habits

Beaupré revealed YouTube’s system may show different kinds of content depending on whether someone is watching in the morning or at night, on a mobile phone or a TV:

“The recommendation system uses time of day and device… as some of the signals that we learn from to understand if there’s different content that is appealing in those different contexts… if you tend to have a preference for watching news in the morning and comedy at night… we’ll try to learn from other viewers like you if they have that pattern.”

Fluctuations In Views

Creators often worry if their views dip, but Beaupré suggests this can be a natural ebb and flow:

“…the first thing is that that is natural… it’s not particularly reasonable to expect that you’re going to always be at your highest level of views from all time… I would encourage you not to worry about it too much…”

He also recommends comparing metrics over longer periods and leveraging tools like Google Trends:

“…we do see seasonality can play a role… encourage you to look beyond… 90 days or more to kind of see the full context.”

Multi-Language Audio

Many creators are exploring multilingual audio to broaden their audiences.

Beaupré highlights how YouTube has adapted to support dubbed tracks:

“…we needed to add some new capabilities… aware that this video actually is available in multiple languages… so if you’re a Creator who’s interested in extending your reach through dubs… make sure that your titles and descriptions… are also uploaded [in] translated titles and descriptions…”

He also emphasizes consistency:

“We’ve seen in particular creators who dub at least 80% of the… watch time… tend to have more success than those who dub less…”

LLM Integration

Looking to the future, large language models (LLMs) enable YouTube to better understand video content and viewer preferences.

Beaupré says:

“…we’ve applied the large language model technology to recommendations at YouTube to… make them more relevant to viewers… rather than just memorizing that this video tends to be good with this type of viewer… it might actually be able to understand the ingredients of the dish better and maybe some more elements of the video style…”

Beaupré likens it to an expert chef who can adapt recipes:

“…we want to be more like the expert chef and less like the… memorized recipe.”

Key Takeaways For Creators

Here are the top takeaways from their 21-minute conversation on the YouTube recommendation system.

  1. The recommendation system is about “pulling” content for each viewer, not pushing videos universally.
  2. Metrics like CTR and watch time matter, but satisfaction (likes, dislikes, surveyed feedback) is also essential.
  3. YouTube can resurface older videos if renewed interest emerges.
  4. Time of day and device usage influence recommendations.
  5. View fluctuations are normal—seasonality, trending events, and external factors can all be at play.
  6. Dubbing and translated titles may help reach new markets, especially if a high percentage of your content is available in the same language.
  7. Large language models empower more nuanced understanding—creators should stay attuned to how this impacts discovery.

Watch the full interview below.

YouTube plans to share more updates at VidCon later this year.

Featured Image: Mamun_Sheikh/Shutterstock

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Jan 27 2025
DeepSeek-R1: The Open-Source AI Challenging ChatGPT via @sejournal, @MattGSouthern

DeepSeek-R1 is a new AI reasoning model from the Chinese company DeepSeek.

Released on January 20, it offers a cost-effective alternative to ChatGPT.

Here’s why it’s DeepSeek-R1 is trending across the web right now.

Key Features

Human-Like Thinking

DeepSeek-R1 has advanced reasoning skills that help it solve complex problems in math, logic, and coding.

People praise its ability to mimic human-like thinking. It breaks problems down into smaller steps using a “Chain of Thought” (CoT) method.

As it processes its responses, DeepSeek-R1 can adjust answers in real time and experience “aha” moments while solving tricky problems.

Here’s a screenshot from DeepSeek’s research paper (PDF link) demonstrating where this moment occurred:

Screenshot from: DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via
Reinforcement Learning, January 2025.

Here’s another screenshot more representative of what you’ll likely see when you use the web interface. This is DeepSeek’s thought process when presented with an SEO-related question:

Screenshot from: chat.deepseek.com, January 2025.

Its chain of thought continued for numerous paragraphs before finally generating a response.

Open Source

DeepSeek-R1 is an open-source model released under the MIT license, which means anyone can use and modify its code.

This openness makes DeepSeek-R1 appealing to businesses, startups, and developers seeking affordable AI solutions.

Lower Development Cost

While companies like OpenAI have spent hundreds of millions to develop their models, DeepSeek-R1 was reportedly built with a budget of just $6 million.

DeepSeek achieved this by using data more efficiently and applying reinforcement learning strategies.

This cost-efficiency was achieved by optimizing data usage and applying reinforcement learning strategies in a novel way that departed from conventional supervised fine-tuning processes typically used to train large language models.

This reduced the need for large amounts of computing power, making it more affordable for end-users.

Affordable Pricing

DeepSeek-R1’s competitive pricing is another factor contributing to its growing popularity.

It’s completely free to use through chat.deepseek.com. And if your machine has the necessary specs, you can also run the model locally on your computer at no cost.

For those without such resources, DeepSeek offers a cloud-based API service at prices far below industry standards.

Additionally, DeepSeek offers a cloud-based API service. Accessing the model through this API incurs costs, but the pricing is notably lower than many competitors.

Is It Any Good?

While DeepSeek-R1 is praised for being affordable and open-source, opinions on its performance vary.

Many benchmarks show it performs on par with OpenAI’s o1 model in areas like logical reasoning and problem-solving.

While DeepSeek-R1 may have unseen limitations, it’s a helpful option for tasks requiring systematic, step-by-step reasoning.

Its open-source nature allows for rapid iteration, making it a dynamic and evolving tool.

What People Are Saying

The release of DeepSeek-R1 has sparked widespread discussion about its potential to democratize access to AI.

The model’s launch also carries geopolitical significance.

Analysts view DeepSeek-R1 as a demonstration of China’s advancements in AI, particularly in light of U.S. technology export controls.

By achieving competitive results with a fraction of the resources, DeepSeek highlights the growing global competition in AI.

Community Reactions

Here’s a roundup of discussions you may have missed over the weekend:

Looking Ahead

DeepSeek-R1 represents a milestone in the AI race, offering a high-performance, cost-effective alternative to established tools.

While it may not yet outperform its competitors in every aspect, its affordability and accessibility position it as a transformative tool for many applications.

Broader Market Impact

The release of DeepSeek-R1 is impacting global markets, particularly in AI and technology. After its launch, tech stocks experienced sharp declines as investors reevaluated the need for large hardware investments.

Nvidia, for example, lost over $300 billion in market value, the largest single-day loss for any company.

This is a developing story…

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Jan 27 2025
Should You Still Use WordPress? via @sejournal, @alexmoss

The last year has been quite eventful within the WordPress ecosystem, marked by discussions and disputes that have prompted some to question the long-term sustainability of the platform and consider exploring alternative solutions.

However, when you dive deeper into these concerns, they pale in comparison to WordPress’s enduring strengths as a product and its unmatched versatility in the CMS space.

Market Share Is Sustained

The first version of WordPress was released on May 27, 2003. Its unique architecture, combined with it being open source, saw a surge in popularity – now dominating (as of December 2024) 43.7% of the CMS market share.

This growth has also been steady despite the emergence of other CMSs including Shopify, Wix and Squarespace. But none of these are open-source.

Not “Just Another” CMS

WordPress’ unique architecture, which allows plugin and theme extendibility, combined with the power of open-source, means it can scale far beyond the blogging platform it was originally.

This means themes could be built for end-users without them having to necessarily understand HTML or CSS and plugins made by third-party developers that could extend and scale the core platform in limitless ways.

Over the years, I’ve built so much with WordPress, including forums, job boards, educational and learning-based portals, ecommerce sites, communities, comparison engines, and scaled themes.

Our clients have ranged from people performing small side hustles and launching startups to managing hundreds of installs on a custom-built server for scaling sites for different global regions and building custom APIs using WordPress to scale activity.

No other CMS provides this flexibility – with any alternatives only doing so with a huge cost and technical debt.

Extendibility [Mostly] Without Limits

While I’ve been involved in building many things with WordPress, the concept of third-party plugins paved the way for trusted extendability within the CMS.

The emergence of free and premium plugins in the WordPress ecosystem has created its own niche, with over 59,000 free plugins available within the official directory – and this does not include the thousands of plugins available away from the repo.

When I discovered WordPress in 2009, I realized it wasn’t just a blogging platform – and, more importantly, it was the most cooperative to SEO best standards. I published my first of numerous plugins in October 2010.

In 2013, I co-founded an agency with WordPress development as one of its core offerings where we have worked on thousands of WordPress sites. Whenever we received an inquiry or pitched for anything to build, WordPress was always the CMS that provided the best solution.

It’s also so easy to get started with WordPress, and I advise anyone who wants to extend their knowledge to do so through experimentation (I talked about it at BrightonSEO a couple of months ago)

A Truly Passionate Community

Another reason I loved WordPress was when I discovered that the community’s massive support helped the CMS progress.

Like the SEO community, the WordPress community is extremely engaging and supportive, not just to help solve issues and help develop the CMS overall, but also there’s a lot of support for people’s professional and personal development.

Away from the extensive resources that WordPress provides through its documentation and forums, the WordPress community thrives all year round through its WordCamp meetups worldwide and participates in other communities, including WordPress chat and PostStatus. There are also numerous podcast series to follow, including Do the Woo, WP Product Talk, and WP Builds.

This community is extremely supportive and resilient to changes, which in turn helps the development of WordPress core, which has been instrumental in shaping the future of website creation, production, and improvement.

The community also gives back in ways I haven’t seen in other verticals.

You Own Your Site And Data

You’d think this would be obvious, but it isn’t. Remember, WordPress is open source. Not only does this mean that the core product is completely free and supported by the community, as already mentioned, but it is also your property.

To now compare this to Shopify, Wix, and Squarespace – these other CMS platforms own your site!

While people may believe there are inherent risks with WordPress, I’d ask you what would happen to your site if, for example, Shopify were to close business tomorrow.

The answer is simple – your site would cease to exist. Then what? If WordPress were to stop development forever from today, you’d still be in the same position and still have your website, content, and data – all of it. What do the other CMSs offer?

As another layer of freedom and risk mitigation, the choice of using WordPress as a CMS is also independent of where you choose to host it.

If for whatever reason you want to migrate your site from one host to another you have the freedom to do so whereas closed source platforms not only own the website you produce with them, but also the server where it resides.

Do The Recent WP ‘Disagreements’ Present A Risk To WordPress?

TLDR – no. The situation does not affect the functionality of WordPress as a CMS. WordPress remains a stable, reliable, and widely used platform, with no indication that its long-term sustainability is at risk. The CMS itself is unaffected and continues to thrive. If you want to read more about the current discussions and disagreements impacting WP leadership, you can read articles such as this and this to gain more insight.

Other Options?

Still skeptical about WordPress? OK, what are your other options?

While other CMS platforms can perhaps be a good alternative to a “standard informational site”, or a site that has no customization requirements at all from the normal out-of-the-box functionality (which eventually happens for every site that starts to scale in any way), you have to make very informed decisions about whether it’s actually worth it – and what the problem is that you believe you’re solving.

Some questions I’d ask myself:

  • Is the CMS open source? If not, what do I own?
  • Is there a strong form of community and support?
  • Does it play nicely with third-party connections and APIs you intend to use?
  • Can you scale the site in the way you want?
  • Can you truly control output on the front end?
  • Does it adhere to SEO best practices?

If any of the answers above are a “no” then you need to understand the risks of those issues before considering any migration, as you may find that the risks of the alternative outweigh anything that WordPress would.

A couple of months ago, I decided to research several open-source CMSs to see if any other platform could compete with WordPress and its capabilities. Unsurprisingly, nothing came close.

TL;DR

WordPress is here to stay and is still the CMS I’d advise in 99% of cases.

It’s safe, supported, robust, future-proof, and open source.

Whilst other CMS platforms can offer some solutions to smaller or simpler sites, I am yet to be truly convinced that they pose any considerable risk to their future or their role in the future of websites.

More resources: 

Featured Image: Krakenimages.com/Shutterstock

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Jan 27 2025
Smart Bidding In Google Ads: In-Depth Guide via @sejournal, @brookeosmundson

Imagine running campaigns that adjust bids perfectly for every auction, targeting the right user at the right moment.

That’s the promise of Smart Bidding in Google Ads.

For PPC marketers, especially for beginners, Smart Bidding can feel like an enticing but sometimes overwhelming tool.

Between algorithm updates, new automation options, and ever-changing PPC best practices, it’s easy to lose sight of how to maximize its potential.

In this guide, we’ll explore what Smart Bidding is, how it works today, and the actionable strategies you can use to get the best results. Whether you’re new to automation or looking to fine-tune your approach, this article is here to help.

What Is Smart Bidding?

Per Google’s definition:

“Smart Bidding refers to bid strategies that use Google AI to optimize for conversions or conversion value in each and every auction.”

Unlike manual or rules-based bidding, Smart Bidding uses data signals – like device type, time of day, location, and even user intent – to determine the optimal bid for each auction.

Some of the key Smart Bidding strategies include:

  • Target Cost Per Acquisition (CPA): Sets bids to help you get as many conversions as possible at your target cost per acquisition.
  • Target Return on Ad Spend (ROAS): Focuses on maximizing conversion value at your desired return.
  • Maximize Conversions: Aims to get the highest number of conversions within your budget.
  • Maximize Conversion Value: Optimizes for the highest total conversion value, perfect for campaigns with varied transaction amounts.

These strategies are invaluable for streamlining campaign management, saving time, and improving results.

However, they work best when paired with a clear strategy and enough data points to make sound decisions.

When Should You Use Smart Bidding?

Smart Bidding isn’t a one-size-fits-all solution. Choosing the right strategy depends on your campaign goals, audience, and available data.

Here’s when each strategy shines, along with real-world examples to help you decide:

Target CPA

Target CPA is perfect for campaigns where controlling the cost per lead or conversion is crucial, such as lead generation.

For example, a SaaS company running a campaign to drive free trial signups wants to maintain a $50 CPA.

By setting this target, Smart Bidding adjusts bids to focus on leads that are more likely to convert within that range, while ignoring auctions where conversion costs might exceed that goal.

Target ROAS

This Smart Bidding strategy is ideal for campaigns where profitability matters more than the number of conversions. Typically, most ecommerce businesses would opt for a ROAS strategy.

For example, say an online retailer selling high-end electronics has a goal to maintain a 400% ROAS (four times return on every dollar spent).

Using Target ROAS, the algorithm prioritizes auctions for users likely to generate higher-value purchases, such as customers buying laptops, while de-emphasizing bids for lower-margin items like accessories.

Maximize Conversions

Try using this Smart Bidding strategy when you have a set budget and want to maximize the total number of conversions, regardless of cost per conversion.

It’s especially effective for brand awareness or expanding into new markets.

For example, say, a non-profit organization aims to maximize email signups for a new awareness campaign.

Since the focus is on volume rather than cost efficiency, Maximize Conversions helps them get the most signups possible within their budget.

Maximize Conversion Value

This strategy is best for campaigns with varied transaction values, where the goal is to optimize for total revenue or high-value actions.

For example, a luxury travel agency advertises vacation packages ranging from $5,000 to $20,000.

By using Maximize Conversion Value, the campaign prioritizes auctions for customers likely to book premium packages, even if they cost more to acquire, rather than focusing on smaller bookings.

Common Pitfalls Of Smart Bidding

Smart Bidding is a powerful tool, but it’s not immune to challenges. Understanding potential pitfalls can help you avoid costly mistakes.

1. Insufficient Or Incorrect Data

Smart Bidding relies heavily on historical data to optimize bids. Campaigns with low conversion volume or incomplete tracking often confuse the algorithm, leading to poor performance.

For example, if you have a campaign that only gets 10 conversions in the past 30 days, it may not be best to go all in on Target ROAS or Target CPA strategies until it gathers more data.

With only a handful of conversions every month, the algorithm lacks enough data to predict future outcomes, resulting in missed opportunities or over-aggressive bidding.

For new campaigns, consider using Maximize Clicks first to gather enough traffic to your website, allowing the algorithm to learn faster and gain more historical data.

2. Misaligned Goals

Using the wrong bidding strategy for your campaign objectives is the easiest way to derail your campaign.

For instance, Target CPA may not be suitable if profitability (ROAS) is your primary goal.

In this hypothetical example, say a retailer mistakenly applies Target CPA to a holiday campaign, aiming for a $20 CPA, even though their products have a $200 average transaction value.

That strategy drives volume, but at the expense of profitability.

Make sure to clearly define your campaign’s primary objective (lead generation, revenue maximization, etc.) and choose a Smart Bidding strategy that aligns with it.

3. Overlooking The Learning Phase

Every Smart Bidding strategy has a learning phase where performance may fluctuate as the algorithm adjusts.

Making changes too soon can reset the process and waste budget.

Say you just launched a campaign with a Target CPA strategy, only to switch it to Maximize Conversions just one week later due to inconsistent results.

This prevents the algorithm from stabilizing and optimizing for long-term success.

Allow one to two weeks (or longer for low-volume campaigns) for the learning phase to complete. Monitor performance, but avoid major changes during this period.

4. Ignoring External Factors

While Smart Bidding is highly adaptive, it can’t predict seasonal trends, promotions, or external market shifts without proper input.

Make sure to use Google’s seasonality adjustment tool to account for temporary shifts in user behavior during sales or promotions, or even national events that could change a user’s online behavior.

5. Underutilizing Advanced Features

Many advertisers set up Smart Bidding, but fail to use advanced options like bid simulators, audience layering, or custom conversion values.

This limits their ability to optimize performance.

Try testing out some of these additional campaign or ad group layers to understand the potential outcomes, and use audience insights to refine targeting.

Best Practices For Smart Bidding Success

Smart Bidding can be a game-changer in the results of your campaigns, but it’s not a magic wand.

To get the most out of this powerful tool, you need to pair automation with thoughtful planning and regular oversight.

By following these tried-and-true best practices, you’ll not only improve campaign performance but also avoid the common pitfalls that trip up many advertisers.

1. Feed The Algorithm With Clean, Accurate Data

Conversion tracking is the backbone of Smart Bidding. Errors in tracking or unverified conversions can lead to misguided optimizations.

When fed with clean and accurate data, the algorithm has the best chance to produce fruitful results.

But when fed with inaccurate data points, your Smart Bidding strategy will wreak havoc on your performance.

Garbage in, garbage out.

Be sure to regularly audit your conversion tracking setup. Ensure every key action (purchases, form submissions, calls, etc.) is tracked accurately and attributed correctly.

For ecommerce campaigns, make sure to include transaction values to correctly use Maximize Conversion Value or Target ROAS strategies.

2. Set Realistic Goals

Unrealistic CPA or ROAS targets can choke the algorithm, resulting in limited impressions or poor bid adjustments.

If you’re not sure what to set your campaign targets at, review historical campaign datasets to set achievable targets.

For example, if your average CPA is $50, don’t set a Target CPA of $20 right away. Start closer to your historical average and adjust gradually.

This also pertains to your daily budget. If your daily budget is only $50 but your average CPA target is $50, this will severely limit ad serving because it’s holding back finding the user most likely to convert.

3. Layer Audiences And Signals

While Smart Bidding works on its own, adding audience segments or demographic layers can give the algorithm more context.

Try using remarketing lists, in-market audiences, and customer match data to guide Smart Bidding towards higher-value users.

You can add audience segments as “Observation Only” to start with if you don’t want to narrow on those users specifically yet.

Depending on their performance, you can always adjust your bids up or down, or even exclude them altogether.

4. Leverage Seasonality Adjustments

Google’s seasonality adjustment feature lets you signal to the algorithm about anticipated spikes or dips in demand.

Before a major sale or holiday, input a seasonality adjustment to help the algorithm prepare for the surge in conversions.

Additionally, make sure to increase your daily budgets to account for those holiday surges.

5. Monitor Performance With The Right Metrics

Don’t rely solely on Google Ads’ automated suggestions and insights.

Do your due diligence and analyze auction insights, search impression share, and audience performance to identify trends and areas for improvement.

6. Run Experiments To Validate Strategies

Testing is critical to understanding what works.

Google Ads Experiments allows you to split test Smart Bidding strategies without risking your entire budget.

For example, say you’ve been running a campaign on Maximize Conversions, but are looking to narrow in on a specific CPA target.

You can set up an experiment to test a Target CPA strategy against the Maximize Conversions to see what performs better for your goals.

That way, you’re not dramatically shifting the behavior of the account overnight and introducing a lot of volatility into performance.

The Bottom Line On Smart Bidding

Smart Bidding in Google Ads has evolved to become an indispensable tool for PPC marketers.

Its ability to leverage machine learning and real-time data is unmatched, but like any tool, its success depends on how you use it.

By aligning your strategy with your goals, feeding the algorithm accurate data, and monitoring performance regularly, you can unlock its full potential.

Remember, automation doesn’t mean you’re off the hook – it means you have more time to focus on strategy, creativity, and scaling your campaigns.

With the right approach, Smart Bidding isn’t just smart – it’s transformational.

More Resources:

Featured Image: dee karen/Shutterstock

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Jan 27 2025
BNPL Fuels Supplier, Retailer Growth

Buy-now pay-later loans can boost cash flow for wholesalers and retailers in 2025 and beyond.

Business-to-business sales bring to mind massive deals with million-dollar transactions, but many wholesale brands sell to small retailers, where deals are in the thousands, not millions.

“We have a few different sock brands running on Cin7, and they sell to kiosks and small shops,” said Ajoy Krishnamoorthy, the CEO of Cin7, which makes cloud-based inventory management software, in an email exchange.

“Those retailers place orders that are $1,000 or $10,000 worth and are often seasonally driven — perfect for BNPL,” stated Krishnamoorthy.

Cash Flow

In particular, BNPL for B2B may be a cash flow opportunity for both the supplier and retailer.

For wholesalers, BNPL accelerates cash inflows and reduces credit risk. For retailers, it aligns inventory costs with revenue, provides financial breathing room, and facilitates growth. Both parties benefit, making BNPL a powerful tool in modern B2B commerce.

Wholesalers

Cash flow is essential for manufacturers, brands, and distributors.

The trouble is that many often wait to get paid. Traditional trade credit arrangements have 30-, 60-, or 90-day terms. B2B BNPL addresses the issue by delivering the payment in a few days or less.

Imagine how much more a manufacturer could produce if a $10,000 invoice is paid tomorrow instead of 60 days from now. The business could rapidly reinvest, explore new marketers, or expand its product line.

BNPL mitigates credit risk. Wholesalers that extend trade credit to retailers are exposed to potential late payments or defaults.

Yet BNPL’s advantages come with a cost: loan fees of 3% or more, typically. Sellers can pay the fees or pass them to buyers. Regardless, there is a cost in money or customer relationships.

Retailers

Cash flow is also vital for retailers operating on thin margins. BNPL loans usually offer better rates than credit cards and are relatively more accessible than advances from a bank or finance company.

Loan Feature BNPL Loans Credit Cards Capital Loans
Approval speed Instant or rapid Moderate Slow
Interest rates Often 0% short term 15%-25% 4%-10%
Flexibility High, purchase-specific High, general purpose Low, long-term use
Default risk Low Moderate High

BNPL loans also offer flexibility. Imagine a small sock seller like the one Krishnamoorthy described. The seller decides to augment its online revenue with a kiosk at the local mall but doesn’t know how to forecast inventory needs.

With a BNPL loan, the merchant could purchase for the kiosk, say, five months’ worth of socks for its ecommerce shop. If the new mall location works well and the socks sell out, it is easy to pay off the loan early. If not, the seller can make monthly payments and sell the inventory online.

The interest rate will almost certainly be lower than a revolving charge card.

The example need not be a physical location. BNPL’s flexible payment terms and rapid application process could fuel new online opportunities.

The risk is relatively low, too. Missing a BNPL loan payment may result in penalties but generally avoids the high compounding interest of credit cards.

Finally, the merchant could generate revenue as the merchandise sells — the BNPL loan improves cash flow.

As with any form of credit, BNPL could be abused or misused.

BNPL for B2B

With its potential benefits, BNPL for B2B will likely accelerate in 2025. I’ve seen estimates of 27% growth this year, roughly mirroring the 25% growth projection for B2C.

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