Using Predictive Lead Scoring in Cross-selling Campaigns
Posted: Mon Dec 09, 2024 9:58 am
In this blog, the importance of lead scoring has already been shown in several posts , in order to know at a given time the situation of a certain lead in the sales funnel and thus carry out the appropriate actions on it at all times (whether closing the sale or continuing with the Lead Nurturing process ).
Predictive Lead Scoring is a method for predicting the likelihood of a given lead converting at a given time. It does this by taking historical data from your CRM and available data on lead behavior from lead management platforms, and combining it with other parameters obtained from multiple sources .
The main element that predictive lead scoring systems introduce over traditional calculations lies in the use of data external to those stored from the lead itself, whether from CRM, forms and web browsing or from telephone interaction.
The origin of this external data is in many cases obtained through the activity of a particular lead on social networks, forums, blogs, etc., and may also include not only the activity of the lead itself but also that of other users and/or companies with which it interacts.
For example, let's suppose we have a company that provides support and maintenance for a certain application and we want to offer our services to the part of our customer base that uses said application.
Since under normal conditions, the information stored in the CRM, in addition to the most general data, only tends to include information related to past interactions with the lead, what we would traditionally do would be a campaign (telephone, email, etc.), asking each of our clients if they are interested in us providing them with support for that application.
Contact when the probability of conversion to sales is high
Optimize the resources used for sales with Lead Scoring
The results of a campaign of this type will vary depending on whether our activity is more or less specific, but as far as sales are concerned, they will almost always be below the expectations created , because the targeting has been carried out without data to justify the selection of leads obtained from our customer base.
The introduction of predictive lead scoring models will search among our customer base (in this case it could only be companies) for indications of the possible use (or intention to use) of said application by a company, through different elements obtained, for example, through social networks, such as profiles required in job offers, employee profiles, searches for information by employees, their opinions, etc.
Based on these social signals, we would not only obtain a filtered list of possible candidates, but also a value or score for each of them based on the estimated probabilities of the success of our sales proposal, which will be established in each case based on the predictive lead scoring model used.
In order for predictive lead scoring platforms to be able to link each of the leads in the CRM database with each of the potential prospects in the databases of a given predictive rich people database lead scoring platform, a unique element will be needed that can identify a given lead, which will normally be a telephone number or an email.
Once a specific lead has been identified, all the information about it can be processed through the predictive analysis model applicable in each case, and from the analysis of that information a predictive score valid for the product or service being offered will be obtained.
Increase your sales with Delio
Delio Lead management Platform allows you to create custom flows of actions without technical knowledge
Predictive lead scoring is also applicable to acquisition processes , since these types of platforms can usually work in real time, and the value provided in each case is usually used together with the lead scoring obtained on a regular basis for each prospect, whether it is calculated dynamically or not.
Although one of the theoretical advantages attributed to predictive lead scoring is the elimination of human error when evaluating the location of a particular lead in the sales funnel, we cannot ignore that its fundamental value occurs at the entrance of the workflow of the Lead management platform , and that once inside it, the specific actions carried out by the lead (form, navigation, call, downloads, etc.) will have greater weight than the profile we had of it at the beginning of the workflow.
On the other hand, we have to take into account (at least while this technology is consolidated) that there is not always enough information from external sources to evaluate a particular lead, or that said information may be valid for certain products or services, while not for others; this without taking into account that many times the identification of a user in a unique way, will almost always be partial, as it is common for the same user to use different means of contact depending on the circumstances (various email accounts, work phone, home office, etc.), and different nicknames on social networks that sometimes cannot be reliably associated with a particular lead.
Evolution of technology.
Predictive Lead Scoring technologies and predictive Analytics in general are in an initial stage of development, especially if we take into account the expectations placed on them, which are none other than getting the most out of the sales and marketing teams of each company, so that a certain product and service "sells itself" .
Regardless of the development that this technology will have in the coming years, the benefits it produces are immediate, especially at the beginning of the Workflow, which is where it is generally more difficult to evaluate the lead and in cases where the existence of a large number of leads, and/or a wide range of products and services make it essential to establish priorities in their treatment.
Predictive Lead Scoring is a method for predicting the likelihood of a given lead converting at a given time. It does this by taking historical data from your CRM and available data on lead behavior from lead management platforms, and combining it with other parameters obtained from multiple sources .
The main element that predictive lead scoring systems introduce over traditional calculations lies in the use of data external to those stored from the lead itself, whether from CRM, forms and web browsing or from telephone interaction.
The origin of this external data is in many cases obtained through the activity of a particular lead on social networks, forums, blogs, etc., and may also include not only the activity of the lead itself but also that of other users and/or companies with which it interacts.
For example, let's suppose we have a company that provides support and maintenance for a certain application and we want to offer our services to the part of our customer base that uses said application.
Since under normal conditions, the information stored in the CRM, in addition to the most general data, only tends to include information related to past interactions with the lead, what we would traditionally do would be a campaign (telephone, email, etc.), asking each of our clients if they are interested in us providing them with support for that application.
Contact when the probability of conversion to sales is high
Optimize the resources used for sales with Lead Scoring
The results of a campaign of this type will vary depending on whether our activity is more or less specific, but as far as sales are concerned, they will almost always be below the expectations created , because the targeting has been carried out without data to justify the selection of leads obtained from our customer base.
The introduction of predictive lead scoring models will search among our customer base (in this case it could only be companies) for indications of the possible use (or intention to use) of said application by a company, through different elements obtained, for example, through social networks, such as profiles required in job offers, employee profiles, searches for information by employees, their opinions, etc.
Based on these social signals, we would not only obtain a filtered list of possible candidates, but also a value or score for each of them based on the estimated probabilities of the success of our sales proposal, which will be established in each case based on the predictive lead scoring model used.
In order for predictive lead scoring platforms to be able to link each of the leads in the CRM database with each of the potential prospects in the databases of a given predictive rich people database lead scoring platform, a unique element will be needed that can identify a given lead, which will normally be a telephone number or an email.
Once a specific lead has been identified, all the information about it can be processed through the predictive analysis model applicable in each case, and from the analysis of that information a predictive score valid for the product or service being offered will be obtained.
Increase your sales with Delio
Delio Lead management Platform allows you to create custom flows of actions without technical knowledge
Predictive lead scoring is also applicable to acquisition processes , since these types of platforms can usually work in real time, and the value provided in each case is usually used together with the lead scoring obtained on a regular basis for each prospect, whether it is calculated dynamically or not.
Although one of the theoretical advantages attributed to predictive lead scoring is the elimination of human error when evaluating the location of a particular lead in the sales funnel, we cannot ignore that its fundamental value occurs at the entrance of the workflow of the Lead management platform , and that once inside it, the specific actions carried out by the lead (form, navigation, call, downloads, etc.) will have greater weight than the profile we had of it at the beginning of the workflow.
On the other hand, we have to take into account (at least while this technology is consolidated) that there is not always enough information from external sources to evaluate a particular lead, or that said information may be valid for certain products or services, while not for others; this without taking into account that many times the identification of a user in a unique way, will almost always be partial, as it is common for the same user to use different means of contact depending on the circumstances (various email accounts, work phone, home office, etc.), and different nicknames on social networks that sometimes cannot be reliably associated with a particular lead.
Evolution of technology.
Predictive Lead Scoring technologies and predictive Analytics in general are in an initial stage of development, especially if we take into account the expectations placed on them, which are none other than getting the most out of the sales and marketing teams of each company, so that a certain product and service "sells itself" .
Regardless of the development that this technology will have in the coming years, the benefits it produces are immediate, especially at the beginning of the Workflow, which is where it is generally more difficult to evaluate the lead and in cases where the existence of a large number of leads, and/or a wide range of products and services make it essential to establish priorities in their treatment.