There are a lot of tools that have come up over the past two decades to improve or assist the revenue generation teams in both B2B and B2C organizations. From the start of the ’90s, we’ve seen organizations investing heavily in first-party data collection to analyze and observe patterns that could help them yield better results.
CRM’s have helped organizations in this data collection journey, but our interactions with many leading companies across sectors (Chemical manufacturers, Consulting firms, E-Commerce companies, specialty product manufacturers, and Retailers) has paved the way for few interesting observations:
· Data is being collected in Silos across the organization. Marketing, Sales, Operations, Finance, etc. are looking at data from a unit level & only some of this data is being leveraged to its full potential
· Newly developing companies are slow to identify all the data points that they want to track
· AI & ML algorithms are stronger than ever due to data availability, but very few companies are in a position to adapt quickly (right data collection being a challenge)
Are our BI & CRM solutions, not enough?
While CRM solutions have helped companies track customer activity closely, collect data & BI tools helped them with ready-to-refer dashboards interpreting this data for the Managers; they are a reflection of how the business is, not a picture of how it can be in the future.
So even after having reliable data and BI solutions in place, sales executives and decision-makers still have to rely on their gut and assumptions in predicting future business opportunities. Which impacts the overall business performance.
That’s where Machine Learning powered applications, come to the rescue to predict the next best actions for the executives and decision-makers to help leverage the true potential of the data in helping your business.
How to leverage the potential opportunities & is this even a potential opportunity for my business?
There are few important questions to answer as a business before jumping on the AI & ML train. Is this even a relevant solution for me? Is my business collecting enough data to make a meaningful investment in AI tools? Are the tools even effective? My CRM is already giving me an overview, how can an AI/ML algorithm on top of my CRM add enough value?
These are the questions that most of us have thought of & would like to understand how to go about this change.
The first step is always to understand the nature of your business & how can a prediction algorithm help you better perform. The predictions can be about potential churn, cross-sell or up-sell opportunities, ticket prioritization for better customer support, sales volume prediction, or inventory planning exercise.
Many of the companies that we had interacted with have tried to answer at least 3-4 of the above-stated problems. They have a team of data scientists who put in a lot of hours to deliver reasonable forecasts & they try to optimize the results y-o-y. Few of the companies also tried to implement ML solutions at an individual unit level to leverage the full potential.
How can companies leverage AI&ML tools like Sager AI?
We need to understand that not all businesses can leverage such solutions & it may never be relevant for a niche company from a Sales & Revenue perspective.
But, it becomes highly relevant for products with high volume sales. In one of our conversations with a leading North American Chemical manufacturer, the ability to forecast potential sales can help them plan their inventories, make better usage of time by focusing on the cross and upselling opportunities, reduce churn & better deploy their data analyst resources and reduce the cumbersome spreadsheet workload on the business leadership team.
So it is highly recommended that a Company looking to leverage such a solution needs to find a partner or internal team that can customize the solution for their unique scenario, in other words, it has to be a bespoke/tailor-made solution.
At its peak potential an AI product like Sager AI can help a business with the below use cases:
- Revenue Forecasting
- Customer Churn
- Next Best Offer
- Lead Prioritization
- Case Management
- Pricing Optimization
Revenue Forecasting: Sager AI will project Revenues from existing clients & prospect future billing opportunities across your product offerings/solutions.
Customer Churn: Sager AI will identify & notify businesses of customers who are about to churn through unique behavioral mapping algorithms.
Next Best Offer: Customers are on the lookout for Vendors/service partners who can deliver end-end solutions within that industry. AI tools help build a pipeline of such cross/ up-selling opportunities & start interacting with them automatically using inbuilt outreach* features.
Lead Prioritization: Prioritize leads basis conversion probability. This helps sales teams focus on customers/ leads that are likely to close, thereby allowing them time to focus on difficult to close leads.
Case Management: Sager AI analyses your customer queries through keyword analysis & prioritizes them for you to strategically service your clients without losing their Goodwill.
Pricing Optimization: Sager AI inbuilt solution also helps you optimize your price offering, depending upon the stage of the sale & the kind of services that are on-demand. This helps you stop underselling or over quoting your prices to secure the client.
Do I need a Data Science team to build AI applications (or) the kind of Human Resources required to deploy such solutions?
The idea of product advancements is to simplify the product so that the end-user can use it to its full potential without any manual intervention. AI & ML products at the current stage do not require dedicated resources to reap full benefits. Any company with good data collection & storage records can leverage Sager AI’s expertise to maintain the product while they continue to read the predictive outputs and insights on easy-to-read dashboards.
Thus the need for such products will be a growing requirement in coming years & the number of firms providing such solutions, Although very high is a good indication of competitive product development which will only make the product much better in a short period. AI & ML solutions are a reality and early-stage adopters will be at an advantage, as they’ll be exposed to the basic tech which will help them upgrade quickly over coming years.