The days of a salesman as the person who cold calls and can close in a quickie are quickly coming to an end. Today, software sales is virtually all about understanding customer needs and using increased technology to make them meet those needs through customized solutions. SaaS sales roles are rapidly growing alongside the SaaS industry, and staying ahead of trends and abreast with advancement is the best way to hone your skills as a sales professional, or find the sales roles that are in line with your career goals.
Selling in a SaaS model does not fit the traditional definition of selling. The model is considerably more strategic, collaborative, data-driven, and personalized than traditional sales models. A professional selling SaaS understands each of these areas on a deep level.
Understanding Customer Needs
Understand your customer’s business – The customers who buy the SaaS products and services in use today are not only looking for cheaper, faster, or easier ways to accomplish their tasks and run their business, they are also looking for a great product experience. They are looking to bring their business to the next level by purchasing a service, product, or set of solutions. They will purchase this experience over and over again if they feel like it is worth the price.
Secondly, they will look for a great enterprise-level product. So, if you can show your potential customer that your product is great and meets their business needs exactly, they are much more likely to purchase from you.
Depending on the size of the sale, it can take anywhere from a few hours to several weeks for the sales professional to gather information about their customers.
Understanding your own product
Understand your own products – If you are selling SaaS products, there’s no way around this one. You have to understand the product line your company sells or you’re in trouble. You could be in danger of losing a sale if the customer asks for a feature or customization that you can’t deliver without the help of another team member, or something to that extent. The buck stops with you; so make sure that you are thorough and aware of how each product works and how it can be customized or enhanced.
Making more data-driven decisions
Data-driven decisions lead to positive results – With SaaS sales models, data can be used to find and target the right customers, determine which products to show them based on their needs, and which solutions are best for each customer. It is simple logic that if you know more about your customers and products, the higher the likelihood of being able to sell that product.
Product experience is king
Product experience is king – In a SaaS sales context, product experience refers to how well your company or client’s customers know your product lines inside and out.
Some companies holding SaaS sales roles may be more focused on increasing their product knowledge, while others may have a more balanced approach. Either way, product experts who understand the products they sell inside and out will be able to show a potential customer just how great their solution is.
There are plenty of ways to find new customers for your SaaS products. Traditional methods like cold calling and emailing are dead. Today, the buyer is in control and you can’t force them into buying your product. With that being said, you can use new or old-school methods to build a relationship with a new company or person in a sales role. There are plenty of resources available to find new customers for your SaaS products. It is up to each individual to choose the right strategy for their business and customer base.
Career Booster: Data-driven Decision-making
Another important aspect to survive in a highly competitive technology sales career is being process-driven and data-oriented. The importance of data is ever-increasing, employers have already recognized the need to make more data-driven decisions to increase revenue. This behavior is highly in demand within the sales function. In order to move up the ranks, one needs to become more and more data-driven and hence it is important for a sales professional to analyze data effectively.
Employers encourage sales professionals to have a working knowledge of systems and tools to help them and the organization make more data-driven decisions.
As the tech stack is expanding with new and tailor-made products for sales professionals, it is becoming quicker and effective for non-technical professionals to analyze information. One such product is Conbi.
Conbi is made for non-technical professionals to make data-driven decisions rapidly without using any code. No excel or SQL.
Imagine a scenario where you need a quick report for a sales meeting to discuss your efforts and performance with your manager. You might want to compare the sales of products from last year with this year to see how sales have changed. To do this kind of analysis, you normally need IT professionals to run queries and generate reports in a data warehouse.
The traditional approach is typically reliant on batch processing the data. For instance, you will run the report and then wait for the IT department to provide it to you. If you want to compare with the other sales reports, you will have to manually or programmatically combine them together. In contrast, a modern Self-service BI application like Conbi enables you to simply ask your questions and analyze data without having to be in front of a computer all day or wait for the IT department. Conbi uses conversational business Intelligence, which is a unique mix of Natural Language Processing (NLP) and Artificial Intelligence (AI).
Now let’s imagine you want to quickly create a dashboard and show it to your team to gather feedback instantly. In a classic BI environment, you would need the IT department to build the dashboard. Then you would have to log in to the data warehouse and load it onto your browser (most likely a PC or laptop). If you want to show it in a Web-based format, your report will still be static.
In contrast, Conbi enables users to invite other users to your dashboard screen and ask questions to your data source in natural language. While doing this, you can create new dashboards that include the results of your previous queries. Second, you can easily request reports and visualizations based on any dataset or data source anyone has shared with you, and they can be delivered in different formats such as HTML5, Excel, PowerPoint, or PDF with a single click of a button. Most importantly, you can interact with the data to see additional information in real-time without having to prepare beforehand!
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