B2B Lead Scoring: AI Optimised

In today’s fast-paced digital landscape, effective B2B lead scoring has become crucial for businesses.

And as long as time is a scarce resource the importance of high quality lead scoring will grow. In short all B2B businesses have long lists of suspect businesses. Some businesses will have high tech and effective platforms to not only score the leads ROI but help sales team transition them along your pipeline. In comparison we have seen significant businesses using simple spreadsheets that lack significant thought into lead scoring.

You will know which group you are a part of. Developing good lead scoring practices help streamline sales processes and, consequently, boost conversion rates. All the while saving you time and maximising your sales teams efficiency. And furthermore by leveraging artificial intelligence (AI) and social media platforms like LinkedIn, businesses can innovate their approach to evaluate potential customers.

Understanding the Art of B2B Lead Scoring

First and foremost, it’s essential to grasp the concept of lead scoring in the B2B context. This process involves assigning values to potential customers based on their likelihood to convert. Traditionally, it meant manually analysing various factors. And naturally this meant subjective biases could be interpreted differently. However, with the advent of AI, this practice has evolved into a more sophisticated and accurate science.

The Transformative Role of AI in Lead Assessment

Maybe as of right now AI is more a buzz word to yourself rather than a tool you are actively using. In short AI and the platforms leveraging the technology are trained on massive data sets. Combine this with its ability to analyse the data, identify trends and even converse and report back insights and results. Therefore AI has undeniably revolutionised the way businesses assess and prioritise leads by introducing:

Predictive Analytics: AI algorithms can analyse vast amounts of data to forecast which prospects are most likely to convert. Given that it has analysed conversion trends and can observe interactions it focuses your team where it is ROI positive.

Behavioural Tracking: Moreover, advanced AI systems can monitor prospect behaviour across multiple touch points. Imagine being notified when new buyers take over, or knowing when prospects are looking over your website. This, in turn, provides a more comprehensive view of their interests and importantly intentions.

Real-time Evaluation: Additionally, AI enables continuous updating of prospect scores based on the latest interactions and data points. As above as key changes take place you will become aware allowing for more accurate conversion forecasting to achieve targets.

We know from a recent Salesforce report that the top marketing priority is improving use of tools and techniques. And with the significant opportunity that AI provides, the businesses that get competent will see competitive gains.

Leveraging LinkedIn for Enhanced B2B Lead Scoring

Occasionally even we forget that social media’s exponential growth and even its creation is within our living memory.

However it has come to dominant many aspects of our life. How we choose to communicate with friends and family. And importantly drive our knowledge and decision making on many topics, especially when it comes to purchase decisions.

In our world of B2B LinkedIn is the primary platform. LinkedIn’s professional focus and rich user data acts as an invaluable resource for data gathering.

Here’s how you can utilise LinkedIn, and combined with AI create a powerful tool and platform as part of your B2B leading scoring:

1. Profile Analysis

At first our attention should be on using AI powered tools to search and collate data from LinkedIn profiles. These profiles are rich with data about current and past employments, interests and links to academic attendance. With this in mind the now collated data can (typically) be automatically inputted in to your tech stack of choice. This ensures accurate data that is time relevant.

2. Engagement Metrics

In addition, with the right AI tools you can gain insight to how potential prospects interact with your company’s LinkedIn content. If you want to find out more about tracking prospects intent we have an article that covers tools that help right here. We know that AI can analyse likes, comments (and the comment sentiment), and how content is shared. AI tools can assess how interested potential prospects are and adjust the prospects ‘lead’ score accordingly.

3. Network Connections

Furthermore, AI tools can assess the strength and depth of a link between potential prospects and your company and team members. Knowledge on this level allows personal approaches from the best placed team members, so that an initial positive impact is made. Whether it relates to interests, academia or employment history. Consequently this leads to strengthening the network connections between your team and prospects.

Implementing AI-Optimised Evaluation Techniques

To effectively implement AI-optimised B2B lead scoring, consider these steps:

Data Integration: Make sure the CRM system you use can integrate data from various sources. Can you include data from social media platforms including LinkedIn and ensure data is updated. Without accurate data communication can go to the wrong people or gets lost. And without clear details pipelines become extended lists without ROI focus.

Define Scoring Criteria: Next, work closely with your sales and marketing teams to establish what a high-quality prospect looks like for your business. This is also the point to ensure your KPI’s are linked to your strategy. You do not want to create a sales team KPI’s on account growth when new business is the real requirement. And remember not every prospect is equal.

Identify AI Tools: Following that, embrace the AI-powered tools that align with your strategy and business KPI’s. Tap into the data, the sentiment and get achievable actions to grow turnover. Popular AI-powered tools include:

Leadspace

Leadspace say they want to help you ‘find, create and prioritise closeable business. Again and again.’

At first Leadspace will leverage your historical data. They use this to build their buyer classification engine. Importantly they need their algorithms to understand the businesses you have qualified and also analyse the losses as well as the wins. Now they incorporate AI with its machine learning to analyse the data against 10,000+ data signals. From this point Leadspace will understand your ideal prospect business. And furthermore be able to search, find and communicate lookalike businesses to develop your pipeline.

Infer

Infer is AI lead scoring for Hubspot and focus on the following statement ‘ensuring your sales reps focus on the most promising prospects first’. That is exactly what we want.

It is important to realise that Infer will take your leads data whether from Hubspot, Salesforce, excel, sales reps or website collection forms. Linked with your Hubspot data it can create predictions and an Infer Score related to size of opportunity, time to close and probability to close. Infer will regularly capture and update any changes in potential prospect details, ensuring the focus stays on the best opportunities.

MadKudu

Obsessive about turning buyer signals into actions, is a good thing for sales. MadKudo will create actions for sales reps. All based off scoring leads and accounts. Therefore actions will be based on signal based data, intent and says it will turn ever rep into a best seller.

Initially combining all the data, MadKudo will take signals from any activity, to identify what matters to your sellers. Whether it is social engagement, product usage or web activity. You will have a scoring system that leads to the ‘most likely to convert’ prospects. Additionally, actions now relate to signals, and daily recommended actions given within Salesforce keep sellers relevant.

Train the AI Model: As I have said above there are AI models that once trained on your data create accurate predictions. Importantly they interpret patterns and commonalities, and leverage those against your current prospect data. In fact it takes you away from those previous meetings reviewing excel and team members providing subjective opinions.

Continuous Refinement: Finally, how many times have you observed that the data out is only as good as the data put in. For the purpose of lead scoring AI models can stay up to date with relevant data, bringing updates and changes to keep an accurate lead score. No more chasing old contacts or missing new buyers at that ‘forever’ prospect, only for a competitor to get in earlier.

The Profound Impact of AI-Optimised Lead Scoring

If you were a sports franchisee with a technology that could enable improved performance, whether it was footwear, clothing, equipment or strategy analysis – would you say yes (providing it is within the rules)?

In B2B businesses, providing the team handle actions accordingly then optimised lead scoring will improve results. The software businesses we have included above show the significant improvements possible. So surely, yes, if you were that sports franchisee you would embrace the new technology.

Because creating a more focused revenue team, knowledgeable about who each lead and account is but also what to say will lead to improvements in your sales and marketing efforts.

Conclusion

In conclusion, it is positive for your B2B business to become tactical about incorporating AI. Especially for lead scoring as it can significantly improve prospect discovery and conversion.

Additionally if you leverage AI against B2B social media, such as LinkedIn you have a strong communication tool to access prospect data and communicate to your potential customers.

Armed with AI tools that will analyse large data to provide the right prospects to focus efforts on, collate further data linked to prospect interactions and intent. And ultimately give you the most likely to convert prospects. You stand in a strong position to drive growth and success in the competitive B2B landscape.

Editorial process

Our articles are curated by experts in B2B business with expertise in AI. And are focused on the technological opportunities that exist for B2B businesses.

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James Ambel

With over a decade of B2B expertise across multiple industries and a passion for integrating new technology to elevate his ROI James’ writing allows all of this to come together. His belief is many B2B businesses could maximise their time, focus and ROI to an even higher level.

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