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Traditional or predictive lead scoring: Which is the best choice for your business?

Giving a score to prospects visiting a website is called lead scoring. This is a particularly important process for companies that want to optimize and improve their sales cycle. For this, they can rely on a traditional model but can also turn to a predictive model, based on the use of artificial intelligence. These two strategies ofaccount based marketingPredictive lead scoring, which primarily targets key accounts to generate sales, has both advantages and disadvantages. So, between traditional lead scoring and predictive lead scoring, which is the best choice for your business?

Why implement a lead scoring strategy?

Writing a note to your leads is an important process for a company wishing to develop its business. It allows you to pre-qualify your prospects, making it easier for your sales team to be more efficient. They know who to target and will follow up with the right prospects at the right time.

If you take a closer look at it, lead scoring is mainly used to meet classic needs. Thus, if a company presents :

  • a low conversion rate
  • a long sales cycle
  • misalignment of sales and marketing teams
  • Difficulties in identifying the return on investment of lead generation initiatives.

The latter might be tempted by the idea of implementing a lead scoring strategy. But what would be the results?

  • Improved conversion rate: giving a lead a rating makes it easier to follow up on them. The higher the score, the more likely they will be converted. Logically, the statistics related to sales should also follow.
  • Reduce sales cycle time: Knowing who to contact and when makes it easier to develop an effective strategy. By targeting qualified prospects, you improve the speed at which transactions are completed.
  • Improved relationship between sales and marketing teams: by implementing a relevant strategy, whose objective is to facilitate the transfer of leads between marketing and sales teams, you strengthen the marketing-sales relationship. Some concepts, such as Kanban methodThese tools can help companies to better organize the management of tasks between departments and team members.
  • Facilitate the ROI of lead generation initiatives: thanks to the lead scoring system, you are able to determine more precisely, the assets that will allow better conversion.
Source: https://clickdimensions.com/blog/

However, the more sophisticated the prospect list, the more complex and complicated the lead scoring process becomes. However, implementing such a strategy makes it easier to define a marketing and sales strategy to accelerate the sales funnel and therefore improve your sales.

Predictive lead scoring: what is it?

If the traditional lead scoring is an excellent way to rate and classify the prospects visiting your website, the process is long to set up. Indeed, it is necessary to manually define the conditions and criteria that will allow a prospect to obtain a good rating or not. The criteria are very numerous. 

In addition to demographics (age, gender, geographic location), you also need to base your customer profile on activity. This is a manual and time-consuming process, especially if your customer database is composed of tens, if not hundreds of thousands of pieces of information that you hold or will retrieve after having created a professional website.

However, predictive lead scoring allows you to address these issues. Thanks to the use of artificial intelligence, it is very simple and quick to define the criteria to be selected and the data that will be retrieved. Thanks to big data and machine learning, AI can automatically classify new prospects and allow sales teams to better follow up and follow up on them, especially through emailing.

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Source : https://www.upnet-agence-digitale.com/lead-scoring-definition-avantages-et-modele/

Differences between predictive & traditional lead scoring

Obviously, predictive lead scoring and traditional lead scoring have their own specificities. While predictive models seem to be best suited for frequent use, in the sense that they can save a lot of time, they usually work on a one-size-fits-all system. This means that AI predictions do not take into account possible changes.

So if your company changes its niche market, the impact on the model and the scoring system will be quite significant. It will be flawed and could lead to some discrepancies between marketing and sales teams, who may not really know where to turn.

Added to this is the fact that the predictive system will never render a perfect result. That's why it can be interesting to focus on both models, creating a calendar of the information you want to use, making sure that the results remain consistent and that the targeted goals are achievable. The idea is to allow both marketing and sales teams to align in order to target the prospects deemed ideal by emailing. The work done by artificial intelligence will then confirm the strategy in place. A set that allows to accelerate the increase of its revenues.

Things to consider before implementing predictive lead scoring in your organization 

There are several things to consider before implementing predictive lead scoring in your organization:

  • Timing: This is an essential criterion. Indeed, it is essential to know how long your manager has been taking action with your company's assets. In this sense, recency allows you to evaluate and prioritize current activities instead of wasting time looking for prospects that are more than 2 years old.
  • Frequency: this indicator allows you to rank the leads according to the frequency of action. In other words, the more active the lead is on your web page (login, registration), the higher they will be ranked. The leads ranked at the top are the ones that the sales team must imperatively target.
  • Online + Offline Activity Rate: Actions taken by prospects, whether online or offline, are important and can help you better understand the prospect. Indeed, marketers will discover, for example, how a person likes to consume certain information. This allows them to create more optimized and targeted content based on the results.
  • Job title: The job title of the prospect noted allows to learn a lot about the situation within a company, the decision makers and the budgetary authority of the person. Keeping track of the prospect's job title will help sales teams shape a suitable pitch to close the deal faster and easier. This is why the identity and customer access management is very important.
  • Industry: like job titles, the industry field helps align your product and/or service with companies that have been successful with you in the past.

Of course, this is only the tip of the iceberg. The criteria mentioned above are the main ones to take into account. However, each company has its own specificities and its own objectives and each one is free to enhance and optimize its research in order to obtain information that it deems more relevant and, above all, more effective.

Conclusion Lead scoring is a relevant and efficient process that allows a company to better understand which prospects are likely to buy a product or subscribe to a service, as quickly as possible. To do this, two methods exist, the so-called classic method and the predictive method. Of course, other strategies exist, such as the use of CRM software to optimize and automate certain tasks in order to save time and better focus on other missions with higher added value.

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