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EC Enterprise Applications

WeaveGrid gets $35M Series B to help electrical grid cope with coming wave of EVs • ZebethMedia

Today, the electrical grid works because utilities have a time-tested playbook. They may not know exactly when you do your laundry, but they generally know washers and dryers run more in the evenings or on weekends. Air conditioners wind up when temperatures soar, and more lights click on during the dark winter months. But in the coming years, that playbook is going to go out the window. Renewables will reshape the grid, but EVs will present the real challenge. Utilities may know how many solar panels and wind turbines are hooked up, but what about how many EVs get plugged in every night? They might have a rough estimate at best. That’s where WeaveGrid comes in. The company’s enterprise SaaS serves as a platform integrating data from utilities, automakers, and drivers to help utilities manage the load that EVs place on the grid. This data will be increasingly important in the coming decade, when up to half of the U.S.’ 280 million vehicle fleet is predicted to become electrified. WeaveGrid hopes not only to help utilities plan for new generating capacity, it also wants to assist in identifying where they can most effectively upgrade their distribution infrastructure, which is going to need a significant overhaul. The average age of the grid’s power transformers, for example, is 25 years. “If 280 million vehicles all start charging around the same time at night, it’s going to create a lot of pressure on an aging infrastructure that’s really not ready to handle all of these giant batteries charging in a completely erratic manner,” said WeaveGrid CEO Apoorv Bhargava. To help coordinate millions of vehicles charging — and to ensure they’re ready when drivers need them — WeaveGrid’s platform pulls data from utilities, automakers and even smart EV chargers to build a picture of when and where the grid will need the most power. The company is announcing a $35 million Series B led by Salesforce Ventures, with participation from new investors Activate Capital, Emerson Collective, Collaborative Fund, and MCJ Collective. Existing investors Coatue, Breakthrough Energy Ventures, Grok Ventures, and The Westly Group also invested in the round. It’s Salesforce Ventures’ first time leading a climate tech investment.

Is the modern data stack just old wine in a new bottle? • ZebethMedia

Ashish Kakran Contributor Ashish Kakran, principal at Thomvest Ventures, is a product manager/engineer turned investor who enjoys supporting founders with a balance of technical know-how, customer insights, empathy with challenges and market knowledge. More posts by this contributor Here’s where MLOps is accelerating enterprise AI adoption Remember the cable, phone and internet combo offers that used to land in our mailboxes? These offers were highly optimized for conversion, and the type of offer and the monthly price could vary significantly between two neighboring houses or even between condos in the same building. I know this because I used to be a data engineer and built extract-transform-load (ETL) data pipelines for this type of offer optimization. Part of my job involved unpacking encrypted data feeds, removing rows or columns that had missing data, and mapping the fields to our internal data models. Our statistics team then used the clean, updated data to model the best offer for each household. That was almost a decade ago. If you take that process and run it on steroids for 100x larger datasets today, you’ll get to the scale that midsized and large organizations are dealing with today. Each step of the data analysis process is ripe for disruption. For example, a single video conferencing call can generate logs that require hundreds of storage tables. Cloud has fundamentally changed the way business is done because of the unlimited storage and scalable compute resources you can get at an affordable price. To put it simply, this is the difference between old and modern stacks: Image Credits: Ashish Kakran, Thomvest Ventures Why do data leaders today care about the modern data stack? Self-service analytics Citizen-developers want access to critical business dashboards in real time. They want automatically updating dashboards built on top of their operational and customer data. For example, the product team can use real-time product usage and customer renewal data for decision-making. Cloud makes data truly accessible to everyone, but there is a need for self-service analytics compared to legacy, static, on-demand reports and dashboards.

How to combine PLG and enterprise sales to improve your funnel • ZebethMedia

Kate Ahlering Contributor Kate Ahlering is the chief revenue officer at Calendly, where she leads sales, sales enablement, revenue operations and partnerships functions. Between the changing tides of the economy and digital buying preferences, SaaS companies are under tremendous pressure. Many of these companies understand that 80% of their interactions with buyers occur on digital channels. At the same time, they need to drive profitability to meet investor expectations. The question is: How do they appease customers who want self-service while accelerating profitable growth? While product-led growth (PLG) is a successful strategy, many companies will complement these efforts with sales-led growth (SLG), or an enterprise sales motion, to move upmarket or into a specific customer segment. With the right go-to-market (GTM) architecture in place and effective use of data, companies can make the most of both strategies to accelerate revenue growth. When does it make sense to complement PLG with SLG? Typically, companies follow three patterns when it comes to their GTM approach: It’s important to make sure your pricing and packaging is differentiated between your individual, team and enterprise plans. Product-led: Focusing on the user and their experience with the product as the primary path to revenue. Sales-led: Leveraging traditional marketing and sales methods to reach the buyer or economic decision-maker. This approach may be supported by selected PLG techniques to drive user advocacy. Hybrid: Combining the best of both worlds, with PLG techniques generating awareness and making inroads into prospect accounts, and sales activities driving most of the revenue. With PLG, the product needs to make an impact on the user — and do it quickly. After all, the product is the primary vehicle for user acquisition, retention and expansion. While PLG works best for products with some level of virality, in many cases, you do not have to choose between SLG and PLG. As an example, Calendly’s sales team often talks to customers about how we can help scale the platform to create an even deeper impact within their organizations. We follow a hybrid GTM approach, where PLG provides a critical access point into prospect accounts, and sales drives enterprise expansion and revenue. While PLG feeds the funnel, sales targets end users with influential titles inside the core use case we serve (e.g. VP of sales), where we can drive the most value and business outcomes.

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