Lead scoring is an essential element of improving your sales funnel and overall marketing efforts. It’s a process of examining customers along their unique buyer journey to calculate a score based on their demographic attributes and level of engagement with your brand. The score a customer receives, usually given in actual numerical points, is highly relevant to your marketing and sales initiatives, as it will often indicate whether the person is likely to buy from you or not.
Calculating that score isn’t as easy as it sounds, however, as human error can often lead to inaccurate results – in turn, undermining the effectiveness of your marketing strategy. With this in mind, learning as much as you can about lead scoring is a wise endeavour if you’re entering the field of marketing automation, as it can be a powerful tool when managed by those who know how to use it effectively.
Automated Scoring and Its Importance for Identifying Strong Leads
Every time a lead views one of your web pages, clicks a link, reacts to a post on social media, or interacts in other ways online with your brand, an automated system can be used to register each of those interactions as useful data. Software has been designed to collect that data to help marketers produce a lead score, most typically based upon the frequency and types of interactions a lead makes online with your brand, and on the individual’s demographic attributes.
Demographic-based attributes refer to specific details about a lead, such as the person’s age, gender, the location they’re from, their marital status, education level, income, and much more. In their sales and marketing campaigns, businesses will be looking to target individuals that fit a specified set of these attributes. If a business wants to target young, single, athletic men with a new type of sports product, for example, they will tailor the lead score to reflect those attributes. The more a person fits in with your engagement and demographic targeting, the higher the lead score they’ll receive.
If you’re taking marketing automation courses, you should understand just how important the lead score can be, as it helps marketers and salespeople identify which customers are worth pursuing, and which strategies they’ll develop to follow up with strong leads.
How Marketers Determine Lead Scores, Explained to Those in Marketing Automation Training
Various types of specialized software serve to automate the process of lead scoring—but it’s important for those taking marketing automation training to note that marketers must still be involved in setting up the software so that it rates customer scores according to online interactions deemed to be of a higher value. That value will be based upon the likelihood of a conversion.
Each business will have its own model for weighting the score, usually tabulated by looking at the customer’s demographics combined with specified types of online engagement—such as results from keyword searches, landing page conversions, level of engagement with email campaigns, and more. If the lead is of the age, socio-economic background, and gender the business is targeting, they may receive a higher score. Certain types of online activities are also likely to produce a higher score – visiting a landing page, for example, indicates a stronger likelihood of eventual purchase versus the same person simply skimming through the website. The tabulated lead score becomes extremely useful in determining an agreed-upon strategy for next steps with each customer. Low scoring leads will receive less attention and follow up than those who score high. The model chosen for weighting specified interactions must be revised and streamlined over time to reflect the business’s growth, as well as the changing needs of customers.
Strategies for Getting Lead Scores as Accurate as Possible
Even with sophisticated software collecting lead scores through automation, human error is a constant problem, as the lead score must be weighted, interpreted, and valued by human marketers. The best way for marketers to get around this unavoidable reality is to continually test their model to see how customers are converting. If the model for weighting is consistently leading to improved results after a slight adjustment on one or more parameters, this can usually be taken as a sign that the change was the right call. Keeping a close eye on your metrics will help you know how to move forward, and to customize as you go along for continued optimal results from your lead scoring efforts.
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