Can the organization afford a new hire? AutoQL can help teams find the data to support their next steps.
~4 minute read
Driving revenue is top-of-mind for every team member in an organization. Improving sales strategy is a critical part of enhancing revenue generation overall. One of the ways teams can boost their sales efforts is by hiring new sales talent to bolster the team’s efforts, expand to new markets, and reach more potential customers.
But, before a decision can be made about whether an investment in a new team member is the best path forward, leadership needs to take a look at the current state of the business to determine if hiring someone new is actually affordable and worth the potential ROI.
Using AutoQL, it’s easy to dig into sales and inventory data to figure out if there is enough working capital in the business to hire that new salesperson. Through a process of exploratory analysis using natural language database querying, decision makers will be able to see if there are opportunities to free up working capital by dropping low-performing products or services.
Team members can explore which items they can cut from their inventory and which are costing them money to keep in stock.
With AutoQL, users can simply ask for “Bottom 5 items by sales this year”. For each of the items they’ve discovered, they can immediately ask a follow-up question: “Monthly sales for item X this year”. Then (if the option has been made available to them) they’re able to quickly select a line graph to see whether sales are trending downwards, or if they’re always low for a certain product.
They can also take a look at their inventory for these low sale or downward-trending items by asking: “Quantity on hand for item X monthly”, repeated for all five items. They can see right away if there’s been a recent decline in the number of a particular item they’ve ordered, and if it may be possible to drop that item entirely.
At this point, users will have a clear idea of which products they can drop. But, they won’t want to leave their best customers high and dry.
While low-sellers may be costly to keep around, it’s important that teams keep their customer relationships in mind when discontinuing items. With AutoQL, it’s seamless to continue the exploration into which items the business can say goodbye to without risking churn.
Team members can quickly ask “Top 5 customers” and drill down into each customer to see if they purchase any of those bottom five items. If they have purchased any of the bottom five items, the “analyst” can then take a look at how often that customer has made that purchase. The team member can also ask “Sales by customer for item X” and repeat for the five items to quickly see if an unpopular item is indeed repeatedly purchased by a top customer.
Read more: How to Talk Data with Conversational AI
When teams are able to quickly and seamlessly explore this data, they can confirm whether a taking on a new hire is feasible. This kind of data-backed decision making ensures that this sales strategy will provide the best outcome for the business and lays the foundation for ROI in the future.