B2B Lead Scoring: From Cold Call to Hot Lead

Look at that, you want to optimize your sales strategy and finally become more successful in the B2B environment? If you've already tried to find potential business partners, you probably also know that it can be a real challenge to separate the wheat from the chaff, especially if you already have a well-functioning Inbound marketing strategy in place and can hardly save yourself from incoming leads anymore.

Don't worry, because that's exactly what a corresponding lead scoring system supports us with. It helps us to distinguish the really "hot" leads from the "lukewarm" ones. In addition, you're doing your colleagues from the sales department a big favor by giving them qualified and interested contacts. These in turn are promising for a potential commission. A win-win situation so to speak.

So, sit back, grab a coffee and let's get started together to learn how you can optimize your sales process.

What is lead scoring and how does it work in a B2B context?

First of all, let me explain to you what lead scoring actually means. The term "lead" from the sales environment should already be familiar to you and means nothing else than contact, or interested party for an offer. Score (Engl. for score) on the other hand stands for a rating of this contact.

In summary, this means: Lead Scoring is a method to evaluate contacts based on their readiness to buy. Usually this is done by awarding points for specific characteristics or also behaviors. Leads, for example, who make a request for a demo or trial version, therefore receive a higher score than those who only download a case study, a white paper or a product datasheet.

There are numerous ways to implement lead scoring in practice, e.g. through automated rules, machine learning or even predictive analytics. For example, Predictive Analytics ERP companies support business processes through automation.

However, the goal is always to prioritize exactly those leads who are most likely to buy your product or service and then pass them on to the appropriate sales staff.

In the B2B sector, this makes particular sense because the purchase decision process here takes much longer than in B2C or FMCG. At least I assume that very few impulse purchases are made for tipping loaders or rotary vane compressors.
Most of these processes take several weeks or months and involve several people at potential buyers, a so-called "buying center". It is all the more important to record and evaluate the individual touchpoints and features of these potential customers.

Why is lead evaluation important and what role does CRM play in it?

Scoring of B2B leads is important as it helps you to use marketing and sales activities more effectively. In addition, it helps you to focus on the leads that are most likely to buy a product or service. This can help accelerate the conversion of leads into customers and generally improve the efficiency of the sales process.

A CRM system plays an important role in lead evaluation, as it allows you to store and manage all information about your leads in one central place. In addition, it allows you to automatically evaluate leads by, for example, using rules and algorithms based on the contact information stored in the CRM.

Also, you can record interactions with these, which in turn allows you to continuously improve and adjust the lead scoring. It thus forms the basis for collaboration between sales and marketing teams to more effectively qualify and convert leads.

How can B2B lead scoring increase the conversion rate?

As already mentioned, lead scoring in B2B can help to accelerate conversion by allowing you to focus on the leads that are most likely to buy a product or service. Sales staff are thus enabled to concentrate their efforts on the "hottest" leads. So they don't have to throw themselves on all the contacts that come in and who are probably (still) not ready to buy.

A lead scoring model can also contribute to better align marketing and sales efforts with the needs and interests of your contacts. By automatically evaluating your leads, you can ensure that you are sending the right information and offers to potential buyers. This increases your chances that these leads will actually become paying customers.

By identifying leads with higher scores and prioritizing their approach, you ensure that the attention is on the contacts who are most likely to buy. This in turn increases the conversion rate.

What factors influence B2B lead scoring?

What are now the key factors in lead scoring and what should be taken into account? To quote John Mueller from Google: "It depends". Of course, this all depends on the type of your offer and what information plays an important role for you. For example, if the transport of huge machines is an essential part of your performance, the location of a potential buyer plays a higher role than if you offer a SaaS solution independent of location. Best of all, you have already created Buyer Personas or ICPs (Ideal Customer Profile) and already know most of the criteria. If not, then let me tell you a little secret:

In principle, you can consider two dimensions when evaluating a lead: the explicit scoring and the implicit scoring.

• Explicit scoring: includes all sociodemographic characteristics of a company, which are also referred to as "firmographics". These include attributes such as the company size - which can be assessed based on the number of employees or even annual sales, depending on the benefit, the industry, the geographical location or even the company form. If your offer mainly appeals to young self-employed people or start-ups, this can of course be reflected in other attributes. But you can also specifically ask for the company phase (or research) and include it in the evaluation.

• Implicit scoring: means every measurable behavior of potential customers or certain predefined behaviors. Of course, this does not mean whether someone watches two talk shows before going to bed and eats a bag of chips - we are not interested in this and it does not help us - but rather information about which pages of your online presence someone has viewed and how often. For example, if someone has viewed your page with price information three times or more, you can award a certain number of points for this. Has someone registered for a webinar, then you can award 15 points. This person then also took part in it? Great, another 15 points! A no-show asks for a recording or summary afterwards - well, not the yellow of the egg, but interest is there - 5 points.

These are of course just exemplary factors that can influence B2B lead scoring. The important thing here is that you identify your important evaluation factors for your product or service. Furthermore, you should always make sure that the factors you define are in relation to the so-called BANT criteria:

• Budget: Of course, a corresponding lead should have sufficient budget to afford your product or service.

• Authority: Does the lead have the corresponding decision-making authority to purchase your product or service or does it play a supporting role in the buying center?

• Need: Is there a corresponding need for the lead and can it use your product or service profitably?

• Time: Last but not least, there should be a temporal determinant. So is the investment in your product or service foreseeable or does it lie in the distant future due to pure information search or uncertainties on the part of the lead?

How is B2B Lead Scoring implemented in practical use?

And now welcome to the peripeteia! As soon as you have your evaluation criteria and the individual point values for them together, we now come to the most exciting part in the implementation of an automated B2B lead scoring model.

And don't worry, if you're not completely satisfied with your point values yet, don't worry. Nobody has achieved a perfect setup from the beginning. Besides, the idea is that a lead scoring model is adjustable and continuously optimized.

As you like and as it suits your purposes, of course you can use only explicit or only implicit scoring. I will discuss the implementation of both evaluation dimensions.

First we need in our CRM or our marketing automation platform two corresponding fields that hold the respective score. Ideally directly with the data type "integer", i.e. as "integers". One contains the value for the explicit scoring, which I also like to call "profile score". The field with the implicit scoring I call "engagement score". Which tools you can use for this, I'll list for you later.

We now imagine these two scores as a matrix, the engagement score as the horizontal axis and the profile score as the vertical axis. Both axes also represent the point values from 0 to 100.

Once we have created these, we need rules and algorithms that fill these fields accordingly and continuously update them. For example, if an interested person submits a form and you ask as standard which role this person has in the company, you can award more points for decision-makers than for example for only influencing roles.

Let's assume we have a lead with a profile score of 80 and an engagement score of 20, it would look like this on our matrix.

So far so good, but alone this does not do us much good. Especially when you consider that this should not only happen for one contact, but for all contacts at the same time and of course we also want to use the insights effectively. Therefore, you should now introduce segments as the next step. Do this in 25 steps on both axes, so that there are 16 fields or segments. Segment the profile score from A - D and the engagement score from 1 - 4, so that there are segment designations from A1 to D4.

To divide your leads into these segments, you need a few more rules and another field that contains the current lead score segment. The rules for our previous example look like this:

Engagement Score ＞ 0 and ≤ 25 AND Profile Score ＞ 75 and ≤ 100 = Lead Score Segment A4

So you can divide your leads into segments. Depending on the valuation basis, you can now create rules that your sales department should work through directly (e.g. A1, A2, and B1). Furthermore, you can also use entire segments directly for a campaign. In our example, you have a lead that is a great fit for your product or service in terms of profile, but has not yet dealt with it very much. A call from sales at this point is still too early and you should rather "warm up" the contact with a campaign. This can be an e-mail campaign, for example, on the topic of "Why {insert your product or service here} is exactly the right thing for your company now!" The more the contact then deals with your web presence or your assets, the further this person moves to the right in the matrix and eventually reaches the segment A2 or even A1, which are predestined for a follow-up by sales.

However, if you have leads in the segments D1 to D4, you can simply ignore them, as you know from the collected and automatically evaluated data that they are not relevant to you anyway.

But beware, you are not finished yet! It's important to remember that B2B lead scoring is a continuous process that needs to be checked and adjusted regularly. Only in this way you ensure that it meets your goals and adapts to changed circumstances and requirements.

Best Practices for Performing B2B Lead Scoring

Of course, you want to be effective with your B2B lead scoring model and achieve the desired results. For this, there are some best practices that I would like to give you in the following.

1. Define clear goals:Before you start lead scoring, you need to define clear goals. For example, is your goal to speed up the conversion of leads to customers? Or would you rather improve the efficiency of the sales process?
2. Identify relevant factors:Really only evaluate the factors that are most relevant to you and best reflect your goals. It's important that the factors you use really do influence your lead's buying readiness.
3. Automate: Use appropriate tools and automations to speed up and simplify the process. Use rules and algorithms to automate lead scoring and prioritization. That's exactly what it means: "No, you don't use Excel for this!" ;)
4. Update and adapt:Lead scoring is not a static method. You should regularly monitor the results, analyze them and adjust them as needed.
5. Integration:Integrate lead scoring system into an existing CRM system. This ensures that all your data is stored in a single location and marketing and sales speak the same language.
6. Data protection: Yes, here too a painful but very important topic. Always make sure that you only collect and process data with the corresponding consent of your leads. This affects both the third-party data that is collected via cookies, and the first-party data that you collect directly via forms.

Challenges and solutions in the application of B2B Lead Scoring

Various challenges arise again and again in the implementation of a B2B lead scoring strategy. If you follow the best practices mentioned above, you are already one step ahead. Nevertheless, here are some things that may encounter you in the course of integration.

First I have to mention bad data quality here. I can't emphasize enough how important consistent and continuous data maintenance is. I have often seen that obsolete data or also wrongly configured fields and attributes in the used solutions had some serious interdependencies. These in turn caused a higher workload to adapt the lead scoring to it. To prevent possible loss of data or a "polluted" scoring, here data transformation and consistency within the whole tech stack are the A and O.

But who is responsible for this tech stack? It can be very difficult to set up and manage an automated lead scoring. Make sure that you use the right technologies and have enough time and resources in the form of experienced staff available. We are talking about the “Marketing Geek”, i.e. the Interface between marketing and IT. This position takes care of the successful integration with existing systems and processes and reduces the dependence on external partners or agencies.

To keep your marketing geeks always up to date with the latest technology (in the truest sense of the word), you should also provide access and time for training. Because if anything changes more quickly than my daily attitude towards peanut butter, then it's the technological landscape. ;)

Also, you should always pay attention to sufficient communication and coordination with everything that has to do with lead scoring and the coordination between the marketing and sales department. Ensuring that all stakeholders are informed about the lead scoring system and understand the methods and results can be quite challenging. Ideally, you should regularly conduct training and workshops to ensure the greatest possible transparency regarding lead scoring. Introducing clear processes and communication channels can help to keep both departments always up-to-date.

This brings us to the next point: In order to be successful, the lead scoring system needs to be constantly monitored and adjusted to ensure that it meets your goals and adapts to changing circumstances and requirements. It's also important to take into account the feedback from sales staff and incorporate it into the evaluation criteria in order to continuously improve the quality of the leads.

Last but not least:the success measurement. In order to determine whether the lead scoring model is efficient, you need to measure its performance, set clear goals and define Key Performance Indicators (KPIs). However, note here that not everything you can measure is also a KPI. If your goal is to speed up the sales cycle and it's more about the quantity of leads, then the Customer Lifetime Value (CLV) is initially secondary (and vice versa) for the evaluation of the B2B-lead score model.

Tools and technologies for successful B2B-Lead-Scoring

A successful and always adjusted lead scoring is almost impossible to achieve with manual effort. You can read which solutions in the market bring decisive advantages in the following list:

• Marketing-Automation-Plattforms (MAP):These tools allow you to create the automated rules and algorithms mentioned above to automatically evaluate and prioritize leads. My favorites for this areMarketo Engage, Salesforce Marketing Cloud Account Engagement (aka Pardot), Oracle Eloqua and HubSpot CRM.

• Customer-Relationship-Management-Systems:A CRM system allows you to store and manage all information about your leads in one central location, your "Single Source of Truth". Examples of this are Salesforce CRM, Microsoft Dynamics 365 Sales, and SugarCRM.

• Business-Intelligence-Tools (BI):With these tools, you can monitor and analyze the results of your lead scoring system. For example, you can use Tableau, Microsoft Power BI, looker, or QlikViewfor this.

• Artificial-Intelligence-Tools (AI):If you want it really sophisticated, you can even incorporate Artificial Intelligence and Machine Learning into your lead scoring. Examples of this areCognismorSeamless.AI.

Again at a glance: That's why you should use B2B-Lead-Scoring

In a constantly changing market environment, it is more important than ever to have an effective lead generation and evaluation machine.

Cold calls played an important role in the past in lead generation. With the advent of new technologies and methods, this has changed. Through the scoring model, you can now identify much more precisely and effectively the leads that really have potential, i.e. those that are actually "hot" and have already shown a lot of interest in a product or service. They have already had interactions with a company and are ready for the next step.

In summary, it can be said that B2B lead scoring is an important building block in the sales process. By using lead scoring models, companies can leave cold calls behind and focus on the hot leads to achieve better business results.