Salesloft integrates with IBM watsonx - here's why

Salesloft integrates with IBM watsonx

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Salesloft is no stranger to using AI in its revenue workflow platform. Last year, it announced its new Rhythm platform, powered by its proprietary AI engine, Conductor AI.

But some companies have already invested time, money, and resources in their own AI solutions, and they don't want to give that up to use Salesloft. IBM is one example of a Salesloft customer wanting to leverage its AI engine (watsonx). It integrated it with Salesloft, and now others can benefit from the integration.

Salesloft CEO David Obrand shared a few details about this partnership and talked about the challenges revenue teams face today that platforms like Rhythm and watsonx can do to help.

The biggest challenges for revenue teams?

Obrand argues that revenue teams face two significant challenges: consistency and reliability. Those challenges look different depending on whether you are an account executive (AE), a RevOps leader, or a CRO. He explains that an AE has a quota number they need to meet, and they want to see a path forward that will help them possibly exceed that quota target. That means they need information - the right information at the right time:

That's where an AI-powered workflow can help: ensuring AEs know what to do, when to do it, who to do it for, and why to do it. Without that structure, it can be challenging for them to understand what is most important, and when and how to execute, ultimately impacting whether they hit their revenue number consistently.

Obrand says RevOps leaders need to be able to identify patterns and data. That's hard to do if your revenue team doesn't follow the same processes in their day-to-day responsibilities:

RevOps needs everyone singing from the same hymnal so they can figure out what's working and what's not. With commonalities in execution behavior, the patterns of what is working and what is not will surface faster along with the data to validate the need for optimization, whether it be to the process, messaging, or training/onboarding.

The CRO needs visibility and insight into the business at scale. They need to be able to forecast accurately, but it's more than that. They need visibility into what drives the forecast, including deal gaps, missed workflow, and missed give/gets:

When you look at the distribution of sellers from a performance perspective, the key for many CROs is to determine how to improve the performance of their second tier cohort – those sellers that routinely achieve 75%-90% attainment. The "B players" can be incredibly detrimental to a company's guidance.  

Leveraging an enterprise workflow platform allows CROs to tether the team to a common set of behaviors and insights that, when properly managed, will drive consistent improvement among your B players, ultimately changing the trajectory of a business for the positive. So consistency and repeatability for a CRO is really about adherence to the best practices and responding to the insights such that one can optimize the mix of art and science in the selling approach."

From bloated tech stacks to AI-empowered tech

Revenue teams have a history of creating a bloated tech stack. They've thrown money and systems at teams with no real idea of how to make them work together. The result is a lot of disconnected data silos.

To solve these challenges, some companies moved in the opposite direction, Obrand says, resorting to spreadsheets to manage business and forecasts. However, now they don't have enough data, and what they get isn't timely. 

In Salesloft's State of Revenue Engagement Benchmark Report, 80% of companies rely on their CRM for forecasting, and 50% use spreadsheets. In fact, CRM is cited as the primary tool for a lot of sales activity. Neither of these - CRM or spreadsheets - is the right choice for a lot of sales development work. 

Now, companies are working to strip down their bloated tech stacks, consolidating to save costs but, more importantly, to improve processes and manage business better. That means clean, integrated data (a system of record) and AI-powered seller workflows (a system of engagement), according to Obrand: 

The key is to create bookends in your tech stack with CRM – your system of record – on one side, and a system of engagement on the other side. This system of engagement must be designed and implemented in a manner that provides both insights regarding buyer behavior, while simultaneously guiding the sellers to the appropriate and proven actions that will maximize the potential outcomes. Simplify the tech stack and provide the sellers with a platform they can "live in" throughout the day that provides the data, insights, and tools to execute on all tasks throughout the customer lifecycle.

Helping IBM and other enterprises bring AI to revenue workflow

So, we know there are challenges. Is that why bringing AI into a seller's workflow platform is so important? Obrand pitches: 

We spend more than 2,000 hours a year working, but all the studies show that sellers spend less than a third of that time with their prospects and customers. As a result of our partnership with IBM, our shared customers will be able to harness the power of AI to optimize their day with prioritized workflows, more accurately predict customer behavior, identify potential risks and deal gaps, and achieve their desired business outcomes quicker.

As to how integrating IBM watsonx impacts Salesloft's own AI engine:

IBM is a trusted brand and we know that trust matters to enterprise buyers. While we are building a version of the Salesloft platform with watsonx embedded, it doesn't change the core capabilities of our platform. IBM's revenue team will use the watsonx version of Salesloft and it will also be an available option to IBM customers who choose it.

We have architected Salesloft Rhythm to be plug and play for the enterprise because we want to  ensure that all of our enterprise customers that have massive investments in the big AI providers don't have to diverge from those investments as they leverage our platform.

IBM became a Salesloft customer in 2018, starting with one specific division's SDRs/BDRs. Then, they expanded the platform's use to their AEs. The platform is being rolled out to their entire revenue organization in over 30 countries. Obrand concludes: 

The success they've had using our platform in their digital sales division was the driver behind this expansion which now is being rolled out wall-to-wall across their entire revenue organization in more than 30 countries.

My take

A huge benefit of Salesloft's platform is that it can integrate with different systems, and AI engines are no exception. Many enterprise companies are building large language models (LLMs) using their own data and leveraging AI and NLP to mine the data for more accurate decision-making. Leveraging the work they've already done within Salesloft would be a key decision in using the platform. 

And for those that aren't doing this AI work or are IBM customers, they have the capabilities already in Salesloft, using either watsonx or Conductor AI. 

Maybe the bigger point is that revenue teams - which include marketing, sales, and customer success people - need AI to help them identify the right places to focus their time and effort. They also need a more streamlined toolset. The days of jumping from system to system to figure things out are ending as these new systems bring everything together under one roof.