On When to Bundle... And When to Not

In the run-up to the Netscape IPO in the 1990s, Jim Barksdale famously told investors that "there are only two ways I know to make money in business: bundling and unbundling." Since then, there's been a ton written on how bundling and unbundling theory works [1]. This has been applied both in product strategy and in pricing strategy, which, while related, are often conflated to mean the same thing by many in tech. Recently, I've been getting a lot of questions from founders I work with where we are in the bundling and unbundling cycle. This is my attempt to pinpoint where we are in the market.

There are examples of bundling and unbundling both by incumbents and startups. Established companies like Google, Adobe, and Salesforce add strategic advantages to their products over time, which is natural bundling. Startups like Rippling and Notion leveraged bundling as their main value proposition to compete with incumbents from the outset. On the flip side, Facebook unbundled its Messenger as it became clear single-purpose apps were better suited for mobile. Startups are often born from unbundling core components of larger incumbents with low NPS and just do it better -- Zoom, Slack, Figma, and Airtable all come to mind.

It seems that Jim was right -- there is a lot of money to be made in bundling and unbundling. But, I haven't seen much literature on when one concept should be favored over the other. If we dissect it down to bare bones, it goes back to supply and demand -- new products on the supply side and buyer preferences on the demand side. What's interesting is how each of these will shift based on three factors: economy, tech, and pricing.

The economy

For a long time post-recession and post-COVID, ZIRP (zero interest rate policy) fueled a wave of unbundling in software. Boosted by access to cheaper capital, buyers had an increased willingness to invest in point solutions that offered better user experiences and tailored workflows. Companies were much more open to buying best-of-breed point solutions and piecing them together, instead of purchasing a single, integrated suite of tools that may suffice for most of their workflows. When the heydays of ZIRP ended, CFOs now scrutinized every line item to find cost savings in times of economic uncertainty.

Economic downturns typically push companies to bundle complementary features to increase perceived value. During economic booms, startups often unbundle specialized features to target specific high-value use cases. This cycle of optimizing for price vs. optimizing for product quality isn't new:

Bad economy = buyers optimize for price
Good economy = buyers optimize for product quality

During annual planning, this means conversations between teams and their CFOs look like:

Bad economy = bundling popular and vendor consolidation typically wins
Good economy = unbundling common and point solutions dominate

In the past, point solutions were much better than bundled solutions, though that is quickly changing -- software development costs continue to lower with AI and the bar for software quality has generally shifted up overall. The additional functionality can be critical to many endusers, but the ROI bar is that much higher in a bad economy.

This also rings true in consumer. In good times, we're more likely to pay for multiple subscriptions across a spectrum of our day-to-day needs: Spotify for music, Netflix for video streaming, NYTimes for our news, Headspace for wellness, and many more. In bad times, however, our wallets are stretched and we're much more compelled by bundles like Apple One or Amazon Prime that offer pieces of music, video streaming, news, wellness, etc. for a single, low price.

The tech

On the supply side, the best startups will often tackle incumbents where there's a fundamental change in the underlying tech. With new tech, startups can unbundle specific use cases to create better products that challenge incumbent bundled solutions in the market. This is often fueled by macro themes like the emergence of personal computing (1970s-1980s), rise of the Internet (1990s-2000s), explosion of cloud computing and mobile (2000s-2010s), decentralization and Web3 (2010s-2020s), and prevalence of AI and machine learning (2020s-?).

The rise of the Internet challenged incumbents such as brick-and-mortar retailers, traditional media companies, and centralized information sources. Amazon started with unbundling the retail experience, initially targeting the book-buying experience by moving operations online and eliminating geographical limitations and inventory constraints of physical bookstores. Google unbundled the process of finding and retrieving individual pieces of information, replacing curated directories (e.g. Yellow Pages and Britannica... remember those?) and print sources. Despite their size now, Amazon and Google initially focused on single pain points that were underserved by incumbents and offered a superior unbundled point solution. Of course, nowadays, both of these companies have become horizontal, bundled solutions. But, to Jim's point, that's how companies make money -- by going through this cycle of unbundling and bundling.

The explosion of cloud computing saw a similar trend -- SaaS transformed the software industry by unbundling specific use cases from on-premise, enterprise systems and delivering them as lightweight, cloud-based solutions that enabled new distribution strategies and business models. Salesforce was launched with unbundled CRM functionality from on-premise systems into a cloud-based SaaS model. Dropbox competed with on-premise file servers and cumbersome FTP systems by unbundling a key use case of file storage/sharing for personal and small teams usage from heavy enterprise systems.

Now, with the prevalence of AI and machine learning, I'm increasingly coming across the startups targeting specific pain points that bundled solutions are no longer adept to solve. The "unbundlers" of the past (Amazon, Google, Salesforce, Dropbox) have now themselves become bundlers, as is the natural progression of product strategy and SaaS revenue models that can only grow via cross-sell and upsell after plateauing on organic user acquisition. Examples include conversational AI assistants unbundling knowledge retrieval, AI-first dev tools unbundling code suggestions from IDEs, and AI applications in vertical SaaS that provide alternatives to horizontal, bundled solutions.

The pricing

We've talked about two dimensions that shifts supply and demand to influence the cyclical timing of bundling vs. unbundling for product strategy. However, product strategy and pricing strategy are not the same. Product strategy focuses on features and use cases of the products while pricing strategy dictates how these products are positioned and monetized based on customer willingness to pay. For example, Apple can bundle its ecosystem through integrated product design via unified Apple ID, Continuity, and Airdrop that enhance product stickiness and cross-product utility. But, it can choose to sell its different products as a la carte standalones, as a discounted bundle, or as add-on features.

Price bundling typically combines two standalone products into a single subscription at a discount. The focus is on price advantage, while product architecture is less important -- products can be independent as in the case of the Spotify + Hulu bundle, or can be integrated as in the case of the Disney+ bundle where ESPN and Hulu content is integrated in the Disney+ app.

Bundling and unbundling in pricing strategy is similarly influenced by the economy and tech. In good times, abundant capital drives more unbundling driven by startups with high risk tolerance to take on incumbents with better products. This typically drives both the supply and demand curves to shift outward, and leads to higher equilibrium prices via price increases or higher price-to-value equations. In bad times, less capital deployed leads to lower risk tolerance and fewer startups unbundling. Supply and demand curves tend to shift inward, reflecting the reduced supply of unbundled products and demand for specialized solutions. Instead, prices will stabilize and incumbents leverage the opportunity to extract more producer surplus through bundling.

Today

Where are we today in the inevitable bundling and unbundling cycle? I would argue the current market driven by an influx of AI is experiencing both, driven by rapid development cycles and evolving business models. Given continued uncertainty in the economy and pending deployment of AI in the broader landscape, companies are choosing whether to bundle or unbundle mainly based on market positioning. But, I predict that we are at the start of more and more unbundling as AI makes software development cheaper and faster.

Major incumbents are on the defense. They have largely been integrating AI capabilities into their existing product suites, focused on creating comprehensive bundled offerings in an effort to harness their distribution advantages in an era of change. Their focus is to continue locking in customers by providing a wide range of services within a single ecosystem -- AI tends to be a horizontal layer that has been applied across many use cases in that ecosystem. Most of these products have been sold as add-ons to existing plans, or as part of bundled plans already in place.

On the other hand, more and more point solutions are cropping up to focus on niche AI applications, offering targeted solutions that address specific needs and betting they can offer better experiences with more customization and customer empathy. These have been monetized as standalone products, with more companies experimenting with outcome-based and customized pricing.

Unbundling has a slight edge right now, and buyers are more willing to try new solutions. As the AI market matures and saturates, I'd expect these companies that have unbundled dominant solutions to eventually bundle new use cases as well. Such is the cycle of business. Ultimately, there will be instances of bundling and unbundling regardless of market timing. But, understanding market timing and where we are in the cycle will provide an edge for founders to take advantage of momentum.

Notes

[1] A few great reads:

HBR's How to Succeed in Bundling and Unbundling
Chris Dixon's How Bundling Benefits Sellers and Buyers
Ben Thompson's The Great Unbundling
Shishir Mehrotra's Four Myths of Bundling