What is Dynamic Deal Scoring?
Part of McKinsey’s Periscope software is Dynamic Deal Scoring (DDS). It is an AI-powered deal-scoring system that assesses the merits of a deal in real-time using machine learning, incentives, and governance.
DDS wants to determine how much a deal is worth and ensure that sales team choices are based on facts. By looking at specific deal situations, DDS finds ways for companies to make more money and helps them use dynamic pricing in their sales processes.
Synonyms
- DDS
- Dynamic deal pricing
- Predictive deal scoring
- Sales deal scoring
How Dynamic Deal Scoring Does It
Traditional deal-scoring models use details about the customer, the product, and the price to judge business deals. DDS builds on these models. McKinsey adds advanced statistics to this method, which lets businesses set scoring goals perfect for their needs.
In short, Dynamic Deal Scoring gives price advice in four main steps:
- Name and address: The system figures out what factors matter, such as the size of the deal, its stage, the configuration of the product, and the sales routes it goes through.
- Splitting up: Advanced analytics models, such as K-means clustering and Chi-square Automatic Interaction Detector (CHAID) decision trees, are used in the background for similar group deals.
- Score the deal: After comparing, the deal scoring system gives each deal a score based on its quality and value, along with color-coded price improvement tips.
- Integration of workflow: The deal scores are used in essential sales processes, like changing rewards based on the quality of the deal and sending the deal to the right level for approval.
How Dynamic Deal Scoring Can Help Your Business
Dynamic Deal Scoring is essential in businesses with much competition, where small profit margins can make a big difference.
Here are some of the most important ways that businesses today use dynamic deal scoring:
Onboarding for sales
DDS makes it easier for new sales reps to start by automating the deal review process and walking them through sales workflows. This way, they don’t have to start from scratch and learn everything.
A standard deal-scoring system significantly reduces the time it takes for new sales workers to get up to speed.
B2B prices that change and update in real-time
Real-time pricing (RTP) and other dynamic pricing models can be used with Periscope. This makes DDS’s AI-driven backend an essential tool for utilities, energy companies, hotels, airplanes, and other B2B companies whose prices constantly change.
Taking care of discounts
Dynamic Deal Scoring considers things that affect discounting, like how much buyers think something is worth, new competitors setting different prices, elasticity, and expected demand. This makes deal management easier and makes sure the company makes money.
Sales Management:
Because Dynamic Deal Scoring and the rest of Periscope’s sales AI tools are built into the core selling process, they can also be used in sales management.
DDS can help sales managers show their teams how to sell, give price quotes, and move deals forward. In the meantime, they can monitor measures like the average deal score and the rate of successful sales to devise ways to motivate people to use the system in the long term.
Management of the bid desk and proposals
Managers of bid desks use dynamic deal scoring to get the best bids. The bid desk team can quickly determine which deals are worth chasing and which channels should get their bids when they have a real-time score.
DDS speeds up (and partly automates) the proposal management process for the bid desk team. At the same time, it increases sales efficiency by only sending potential deals that will give the company the best return on investment.
Sales operations on the front lines
The sales rep is probably the most critical person who uses dynamic deal scoring.
DDS helps sales reps quickly find profitable deals, which makes them more productive and helps them make better decisions when giving sales demos, qualifying leads, and making cold calls.
Higher customer satisfaction and better general sales performance are the results. The company’s bottom line stays the same or even goes up.
What are the pros and cons of dynamic deal-scoring?
Dynamic deal scoring has a lot of pros.
- They are making decisions based on data. DDS uses AI-powered analytics and machine learning algorithms to help businesses make intelligent choices based on data rather than guesswork or human bias when evaluating deals.
- More money is coming in. When buyers know how to find good deals and set the best prices, they can make more money, work more efficiently, and get more done.
- They made the sales process more manageable. DDS automates some aspects of the sales process, like deal approval. This lets sales teams focus on more critical tasks.
- They made the sales team work better. Sales teams are more likely to focus on high-quality deals when rewards are linked to deal quality, and deal quality is considered in performance reviews.
Bad Things About Dynamic Deal Scoring
- The difficulty of implementation. It can be challenging and take a lot of time to integrate DDS into current sales operations and systems, especially if they don’t have a lot of IT infrastructure.
- There is a chance that few people will adopt. Some people on the sales team might not like change, especially regarding new technology and ways to judge success.
- You are relying on the quality of the information. How well DDS works depends a lot on the quality of the data that is put into it. If you have wrong or missing data, it could affect how you evaluate deals and set prices, which could make the benefits of DDS useless.
- The cost of implementation. Implementing DDS can be pricey because you may need to buy new technology, get training, and even hire specialized IT staff.
Technology for dynamic scoring
Dynamic scoring technology uses machine learning and predictive analytics to make decisions in real-time. It’s different from other ways of getting deals because it can be used in different situations.
A data-driven dynamic deal advice model does more than look at past data. It also considers micro-market trends like competitive pricing, perceived value, and price elasticity to give sales reps and bid desk managers insights relevant to their situation.
It also works well with setting prices, escalating deals, hiring new salespeople, training them, and managing incentives.
In short, the AI that powers dynamic deal-scoring makes it more flexible than old-fashioned deal-scoring methods. This gives businesses an edge in today’s fast-paced business world.
