Salesforce has been a leader in B2B space since 2001, and Marc Benioff has been one of the key leaders, always pushing innovation forward and making sure that his customer needs were met. VC investments reached dot-com boom levels; competition is fierce, and scaling is not easy. In this post, we will be exploring the future of B2B Software and how companies can win in their category. According to Benioff, companies should aim to be the System of Record, making sure users are engaged and should provide insights that they would not get with other software.
Increasing the Level of Abstractions
THEORY
In his Emergent Layers Theory, Alex Danco (Social Capital), describes a framework to understand how and why we are going into increasing level of abstractions and less friction regarding value delivery.
Rephrasing Alex’s Emergent Layers Theory:
- At the initial state, businesses make money off of points of friction governed by scarce resources (located at level i).
- The nature of competition at the initial layer will lead to customers with jobs-to-be-done related to this resource (at level j) becoming overserved with features, saturation, and expense.
- Meanwhile, these same customers will have higher-order jobs, at level j+1, for which they are underserved. However, these customers’ needs cannot be addressed at level j+1 directly, due to the constraints and points of friction at level i.
- A breakthrough occurs when this scarce resource at layer i becomes abstracted away, thus removing friction, in such a way that it can grow in a scalable way, and becomes abundantly available.
- As a consequence of this abstraction and new scalable abundance of this resource, the old constraints around which profits were made go away. Crucially, the removal of this limitation allows users to be served at the j+1 level need directly, at a higher-order level of value.
- As explained in Disruption Theory, incumbents will initially be incentivized to ignore the new entrants or retreat upmarket, but soon find themselves eclipsed and obsolete.
- Profit and power leave the incumbents gradually and then suddenly; it is redistributed to those serving customers at level j+1 directly.
- Out of this newfound abstraction and abundance, a new scarce resource emerges at layer i+1. Individuals, companies, and institutions that win are those who can master the economics of abstracted abundance of the old resources as well as the scarcity of the new one.
- Over time, this new scarce resource becomes established, accepted, and status quo. The cycle is ready to repeat.
EXAMPLES
On the consumer side, mobile enabled frictionless interaction by being an extension of ourselves.
- Uber is the most prominent example: the system knows where you’re standing and where the driver is. No need to hail, just tap to get a cab. It will charge you automatically at the end of the ride, and it lets you accurately rate the driver.
- Amazon is also a leader in removing friction by innovating on different interfaces: Reducing search time, One-Click Buy Button, Amazon Echo, and Amazon Dash.
On the business side, there are both technological and business factors driving frictionless business delivery.
- On the technological side: mobile, the cloud (AWS), APIs and better developer tools.
- On the business side: the rise of competitive threats, profits squeeze, consumerization of IT. Lots of IT project under delivering which resulted in less confidence in IT being able to deliver significant business results.
Systems of Record
THEORY
In the Saastr podcast episode #011, Ajay Agarwal (Bain Capital Ventures) describes a system of record (SOR) as a software that serves as the backbone for a particular business process. A SOR is very sticky and hard to rip out as it is tightly integrated into the business process.
Ajay gives some guidelines that can be followed to build a sustainable software company
- The more the SOR is at the heart and soul of how a company makes money, the more valuable the SOR will be (e.g. Workday in HR)
- Usually, SOR is the ultimate source of information for a particular business process and thus “record” of critical data. As the ultimate source, other applications have to integrate for their solutions to work (e.g. Salesforce AppExchange)
- The higher the proportions of employees that interact daily or weekly with the application, the more engagement and usage will be high and it will be harder to replace (e.g. Slack)
- SOR should require and benefit from human inputs of some kind as it is more difficult for the next player to take over and replicate the codified knowledge that the user entered into the system (e.g. Enterprise CMS like Sitecore)
- Finally, the SOR should learn and improve over time and be a “system of truth,” used to form the foundation for meaningful business decisions. These two points will be touched upon in the next section.
EXAMPLES
Building a SOR is hard, and it takes time for the company that acquires the software to get value out of it. With the rise of APIs, we have seen companies trying to integrate other apps to reduce time to value and to provide upfront value to their customers. In a recent paper, Hartmann, P. M. et al. studied the data-driven business models of different startups. 73% of the companies use external data sources, 16% use internal and external data sources and 11% use only internal data sources, that is data they create themselves. In the future, I think we will see more companies using both internal and external as it supports user lock-in.
eShares is a great example. They are building a SOR by storing the cap table online and by doing that, they can leverage the customer data to generate 409A valuation.
Another example is Usermind, a unified platform for orchestrating business operations. Usermind is like a Zapier/IFTTT on steroids. They take data from marketing process, sales process and finance process and reconcile everything together. The reconciliation is key. They are generating normalized data that they can use to provide insights to cross-functional business teams.
Systems of Intelligence
THEORY
Boris Wertz (Version One Ventures) wrote an influential post on what he thinks the evolution of apps will be.
The new generation of enterprise apps will differentiate themselves by both the quality and speed of their insights. We’ll see smart be real-time.
Boris thinks that software will evolve along the following framework:
- Reactive Apps: These are web-based tools that give users a way to create the outcomes they need. The app just follows the user’s direction; the user is in control.
- Proactive Apps: The next stage adds a little more intelligence to proactively notify end users of changes in the outcome or other information they should know.
- Predictive Apps: Here’s where machine learning kicks in. These tools use machine learning/predictive modeling to predict outcomes or potential changes to expected results.
- Pre-emptive (Prescriptive) Apps: The last stage in-app evolution is artificial intelligence. Here, the app doesn’t just notify customers of changes in outcomes, but can also take the actions needed based on those changes.
EXAMPLES
From the Hartmann, P. M. et al. (2014) paper, there was 22% of the companies that were doing predictive analytics and 6% that were doing preemptive analytics. We are still in the early day of data science and machine learning. It will be interesting to see how many can move up the stack to Predictive and Preemptive as it requires a lot of data. Data is king in this new world of B2B software.
Coveo, have a technology called Coveo Reveal. Coveo Reveal continuously learns and adjusts based on the intelligence gathered from the community of users’ search behavior to improve the results and experience of the solution. Coveo can present relevant results for a particular user with a specific context, decreasing information search and support cost.
Foursquare offers a Places Database to the enterprise. They provide world-class location data, services, and solutions. With their solutions, they can have insights on particular business and local trends, like the number of iPhones sold or the drop in sales at Chipotle, enabling hedge fund to trade on that information.
Systems of Engagement
THEORY
Sarah Tavel, a partner at Greylock Partners, defines a Hierarchy of Engagement as follow:
LEVEL 1 — GROWING ENGAGED USERS
According to Sarah, what matters is growing the number of users completing the core action and not just the growth of users. The core action is the foundation and essence of the product. Think about sending a message in Slack or creating a document in Quip/Evernote. So you need to both grow the user base and also grow the number of people completing the core actions if you want a healthy product with engaged users.
LEVEL 2 — RETAINING USERS
Once you have engaged users, you need to make sure that they will stick. There are two ways to have users stick.
- Using data to make the experience more engaging. This is done through your System of Intelligence.
- Prevent negative net churn by investing in customer success.
Customer Success has become more important in the last few years with the rise of SaaS and business models relying on recurring revenue. According to Tomasz Tunguz, VC at Redpoint, customer success has many benefits.
- Reduces customer acquisition costs by fuelling word of mouth.
- Increases/stabilizes the market size, because you are not burning through customers
- Good customer success increases account expansion (upsells) which reduces the amount of capital you need to grow
LEVEL 3 — SELF-PERPETUATING
Here, it’s whether the engagement of existing users creates virtuous loops in the product. This is rare (especially for B2B).
- The strongest virtuous loop is a network effect
- User re-engagement through notifications
- Growth through user referral
Here again, the System of Intelligence can help build a virtuous loop because a user will gain more value as they use the system (same-side network effect) and will gain as the system learns from other users (cross-side network effect). A data network effect can be long to kickstart, so you need to make sure that the users win in some ways.
EXAMPLES
Slack is famous for its massive growth in the past year or so. Some even called it the “Fastest Growing Business App in History.”
LEVEL 1 — GROWING ENGAGED USERS
Slack user growth is astronomical, so they are fine on that side.
The core actions of Slack is the act of sending a message. Although we don’t know the growth of the core actions, we know that 1.5 billion messages are being sent each month and users are on the application for 320 million minutes of active usage each weekday, which is a bit more than 2 hours each day.
LEVEL 2 — RETAINING USERS
Slack, by nature of being a messaging application, will retain more users since you need to be part of the network if you want to chat with your coworkers. You can probably go back to Skype for business or email, but the chances are that the users will be more responsive on Slack. Even if Slack is mostly sold through a bottom-up funnel, they have a customer success team for the larger account. For smaller account, Slack numbers speak for themselves, and they have some compelling customers report statistics:
- 32.0% in increased productivity
- 48.6% reduction in emails
- 25.1% reduction in meetings
- 79.0% agree team culture has improved and 80.4% agree team transparency has improved
LEVEL 3 — SELF-PERPETUATING
Slack has two elements of the virtuous loop.
- User re-engagement through notifications (push, email) is happening when a user ping you or ping the entire channel (DON’T). Also, a user that watch a channel is most likely to participate in it when a discussion happens.
- Growth through user referral is happening when an admin is setting up Slack for the corporate account or when your coworkers tell you to join slack
However, we currently think that Slack fails at building a STRONG network effect. We have heard about Uber ditching Slack to go to their competitor Hipchat and heard about “Slack Fatigue.” While this is most likely anecdotal, it could also be a signal of a weak network effect. In a strong network effect, the cost of leaving the system is too big, so you stay in it. They are trying to make it stronger by building a platform and enabling integrations (4,000+ apps developed so far for Slack).
Conclusion: It’s all about reducing Time to Value
On the Saastr podcast, Index Ventures Partner Shardul Shah talked that for his B2B software investment it was all about reducing time to value.
Forrester defines time to value has the time from project initiation until the projection of total business benefits is achieved. This definition emphasizes the tie between technology, business processes, and business goals, leading to a higher alignment between all three.
Winning next-generation B2B software will have both shorter deployment period and quicker business gains.
On one hand, they will move to the upper level of abstractions and remove friction.
This will enable vendors to deploy in a shorter period.
On the other hand, they will have the three components of Systems of Records, Systems of Intelligence and Systems of Engagement.
This will allow the companies that buy their software to gain business value much quicker than with legacy software.
In conclusion, this will create a killer mix of vendors, and we are looking forward to seeing more of those.
