How to automate lead scoring

How to automate lead scoring

Automating lead scoring helps prioritize your prospects objectively and improve your sales performance. Here are the key points:

• What is lead scoring?
  It involves assigning points to prospects based on their actions (content downloads, page visits, social media engagement) and characteristics (industry, company size). This helps identify prospects most likely to become customers.
• Why automate?
  • Time-saving: No need to manually evaluate each prospect.
  • Reactivity: Real-time updates for better decision-making.
  • Tangible results: For example, a company using AI-based scoring increased sales by 27%.
• Role of AI
  Artificial intelligence analyzes complex behaviors, improves prediction accuracy, and adapts scores to local specificities, such as multilingual interactions in Switzerland.
• Key steps to get started
  1. Define your Ideal Customer Profile (ICP): Identify your target customers by analyzing your existing data.
  2. Choose a suitable tool: Opt for solutions like HubSpot, ActiveCampaign, or Salesforce.
  3. Set up scoring rules: Assign points based on prospect actions and characteristics.
  4. Integrate with your CRM: Sync your tools for real-time actionable data.
• Best practices in Switzerland
  • Comply with the Swiss Data Protection Law (LPD) by obtaining explicit consent.
  • Adapt your strategy to local linguistic and cultural specificities.
  • Use Swiss formats (CHF, dates, numbers) for better accuracy.

Automating lead scoring helps maximize your marketing and sales efforts while respecting local specificities. Adopt this method to increase conversions and optimize resources.

The SIMPLEST Way To Build An AI Lead Scoring Assistant (AI Automation)

Steps to automate lead scoring

Creating an automated lead scoring system requires a structured approach. Here are the key steps to implement an effective process tailored to the specificities of the Swiss market.

Define your Ideal Customer Profile (ICP)

The first step is to clearly identify the type of company that will benefit most from your product or solution. As explained by Guido Bartolacci, Head of Product Strategy and Growth at New Breed:

An ideal customer profile is a hypothetical description of the type of company that would derive the most value from your product or solution.

To develop your ICP, analyze your best current customers. Look for commonalities such as company size, industry, geographic location, stage of development, number of employees, annual revenue, or technology tools used. Also gather information on their main obstacles through surveys or feedback from your sales and support teams.

A striking example: in 2017, New Breed adjusted its ICP by stopping targeting "Startup Sams." The result? A 152% increase in average contract size in less than two years.

Once your ICP is well defined, it will be easier to choose the technological tool that suits your needs.

Selecting a marketing automation tool

With an ICP in hand, it's time to choose a marketing automation platform. This should include scoring features and seamless integration with your CRM.

The benefits of marketing automation are numerous: a study shows a 451% increase in , while 49% of companies see growth and 43% of marketers note a better customer experience. In Switzerland, prioritize tools that comply with local data protection regulations and can handle multiple languages.

Here are some popular options:

• ActiveCampaign: starting from CHF 9.–
• HubSpot Marketing Hub: starting from CHF 50.–
• Mailchimp: starting from CHF 9.99
• GetResponse: starting from CHF 19.–
• Salesforce Marketing Cloud: starting from CHF 1'250.–

Takeo Ueno, CEO of NTT DATA Payment Services India, summarizes the importance of this choice:

To optimize our company's marketing automation, selecting the right tools is crucial. We prioritize solutions that seamlessly integrate with our existing systems, empower our teams, and deliver measurable results.

Once you have selected your tool, proceed to configure the scoring rules.

Configuring scoring rules and triggers

Lead scoring is based on assigning points based on prospect actions and characteristics. Spencer Pereira explains:

Lead scoring allows you to identify your most interested prospects based on their engagement with your content. People earn higher points when they take action: opening an email, submitting a form, or clicking a link to a whitepaper.

Start by defining the main goal of your scoring: measuring engagement, qualifying prospects for the sales team, or filtering out irrelevant leads. As Lauren Ryan points out:

Scoring is usually a combination of measured intent and quality. So, does this person want to talk to us/buy from us and is this someone who would be a good fit for our product.

Next, establish thresholds tailored to your sales process. For example, in a system based on 100 points (like ActiveCampaign), you could define:

• Prospect: 10 points
• Lead: 50 points
• MQL (Marketing Qualified Lead): 75 points
• SQL (Sales Qualified Lead): 100 points and above

Associate specific actions with each threshold, such as downloading a guide, submitting a form, scheduling a meeting, or attending an event. Also introduce point degradation to prevent inactive prospects from remaining overvalued. Finally, document all these rules in a clear and accessible guide.

Integration of lead scoring with CRM and sales processes

Once your scoring rules are defined, it is crucial to connect your system to your CRM and sales processes. This connection transforms raw data into actionable information ready to be used by your teams.

Data flow between systems

For your and CRM to work harmoniously, automated real-time synchronization is essential. As emphasized by The CRO Club:

When you integrate lead scoring into a CRM, it's automated and updated in real-time. The goal? Ensure that the right leads receive the right level of attention from your sales team.

Start by mapping and synchronizing data fields between your tools. Implement validation rules to automatically correct inconsistencies. Take the example of Spotify: in March 2023, the company reduced its bounce rate from 12.3% to 2.1% in just 60 days through real-time verification, generating an additional CHF 2.1 million in revenue.

Data format standardization is equally crucial. Ensure that dates, currencies (like CHF), and numerical formats (using commas for decimals) are consistent across your systems. Also, plan regular data cleaning processes to eliminate duplicates and maintain optimal data quality.

Well-executed synchronization not only facilitates data management but also establishes a solid foundation for smooth collaboration between your marketing and sales teams.

Collaboration between marketing and sales

With well-synchronized data, alignment between marketing and sales becomes a priority to maximize scoring efficiency. Ryan Durling, an inbound consultant at HubSpot, puts it this way:

The biggest challenge of lead scoring is not defining how much something is worth in points, it's ensuring that everyone internally is aligned.

To achieve this, start by defining together what a qualified lead is. Your teams must agree on demographic, behavioral, and engagement criteria that identify a prospect ready to be contacted by sales. Organize regular meetings to adjust these criteria based on results.

Establish a continuous feedback system where salespeople share their feedback on the quality of leads received. This information helps refine your scoring rules. For example, if your teams find that a lead who downloaded a specific guide is more often converted, adjust the points assigned to this action.

Through automation, qualified leads (MQLs) can be immediately assigned to the right salesperson, ensuring quick and personalized follow-up. Clearly define responsibilities and transfer moments based on the scores obtained to never let a qualified lead slip through the cracks.

A well-orchestrated collaboration between marketing and sales, supported by reliable data and automated processes, ensures efficient and proactive lead management.

Measuring and optimizing lead scoring performance

Once your scoring system is in place and integrated, it is crucial to measure its effectiveness to ensure long-term results. Without regular monitoring, even the best system may become obsolete in the face of market changes and shifts in prospect behavior.

Key indicators to monitor

To assess the impact of your scoring, focus on metrics that directly reflect its effectiveness. For example:

• Lead conversion rate: measure the percentage of scored leads that become customers.
• Conversion time: identify if your system speeds up the process by quickly identifying prospects ready to buy.
• Cost per lead (CPL): this indicator verifies if automation reduces costs by optimizing resource allocation.
• Customer Lifetime Value (CLTV): well-scored leads should generate above-average value.

Data shows that 80% of marketers have seen an increase in leads after adopting marketing automation software. Moreover, B2B companies using these tools experience an average 10% increase in their sales pipeline.

Also, do not overlook engagement metrics: analyze web traffic, number of page views, or form submissions. These behaviors directly feed into your scoring system and can reveal changes in prospect habits.

Sales Performance Metrics	Priority
Lead conversion rate	12
Cost reduction	10
Number of qualified leads	9

These indicators serve as a compass to adjust your efforts during regular audits.

Regular audits and adjustments

Plan frequent audits to evaluate and adjust your scoring system based on collected data. Start with monthly reviews, then adjust the frequency as needed. These audits help identify discrepancies: for example, if highly scored leads do not convert or if low-scored prospects become customers, it's a sign that your model needs recalibration.

"Accurate lead scoring starts with clean data - I've learned this through experience! Having a solid validation process has helped me catch errors early, ensuring that engagement metrics truly reflect what's happening. I also make it a point to regularly audit my lead database. This not only maintains accuracy but also builds trust with customers."

Take Salesforce, for example: the company reported a 10% increase in team productivity and a 27% conversion rate increase after adopting automated behavioral scoring.

Finally, involve your sales teams: their feedback on the quality of leads received is essential to refine your scoring criteria. These adjustments, combined with regular audits, ensure that your system remains relevant in the face of market changes.

Keep in mind that scoring is a constantly evolving process. Buying behaviors and market dynamics change: plan quarterly reviews to adapt your model to the new realities of your industry. This will keep your system performing well and aligned with your goals.

Best practices for automated lead scoring in Switzerland

For your automated scoring system to work effectively in Switzerland, it is crucial to consider local specificities. Between strict data protection laws, linguistic diversity, and local specificities, several elements deserve special attention. Here are recommendations to adapt your strategy.

Comply with Swiss data protection regulations

Since September 1, 2023, the new version of the Swiss Federal Data Protection Act (LPD) has been in effect in Switzerland. This legislation applies to both Swiss companies and those based abroad, as long as they process personal data of Swiss residents.

For your scoring system, this implies obtaining explicit consent for each data processing. A particularity of the LPD is that it can sanction not only companies but also individuals. Sensitizing and training your teams on the requirements of this law is therefore essential.

"The Swiss FADP modernizes Swiss data protection law and essentially aligns Swiss standards with the European GDPR with a 'Swiss finish' in some areas." - Konrad Meier, Senior Manager, AI Law Leader in Financial Services, EY Switzerland

Here are some key measures to ensure the compliance of your scoring system:

• Maintain a detailed record of all your data processing activities, including collection points such as web forms, social media interactions, or downloads.
• If your company is based abroad, designate a representative in Switzerland to liaise with local authorities.
• Promptly report any data breaches to the Federal Data Protection and Transparency Commissioner (PFPDT). Unlike the GDPR, the LPD requires immediate notification, without a specific 72-hour deadline.
• Ensure that your system complies with profiling rules, especially for automated assessment of personal characteristics.

Adapt your strategy to multilingual audiences

With its four national languages - German, French, Italian, and Romansh - Switzerland is a country where linguistic diversity plays a major role. This has direct implications for your scoring strategy.

Your system must be able to segment leads based on their language region. Communication preferences and buying behaviors may vary by area. Personalizing nurturing workflows tailored to local specificities is essential.

To optimize engagement, configure your system to automatically identify each lead's preferred language, based on clues like geographic location or browser settings.

Integrate Swiss standards and formats

Local adaptation goes beyond language. Your tools must also reflect the formats and metrics used in Switzerland.

• Currency: Display and calculate in CHF.
• Dates: Use the day.month.year format (e.g., 31.12.2023).
• Numbers: Adopt Swiss separators, with an apostrophe for thousands (1'000) and a comma for decimals (1'000.50).
• Time zones: Integrate CET/CEST times in your automations.

Finally, adjust your scoring criteria to reflect the realities of the Swiss market, such as local preferences in segmentation and buying behavior.

By combining these local adjustments with rigorous data management and precise linguistic segmentation, your automated scoring system will seamlessly integrate into the Swiss business landscape.