What defines a qualified b2b lead?

Part
01
of two
Part
01

B2B Sales Lead - Best Practices 1

Useful Findings:

Lead scoring system : Overview

  • For both sales and marketing, lead scoring is the methodology that helps to ascertain the worthiness of leads or potential customers by attaching values to them based on their behavior relating to their interest in products or services.
  • In both sales and marketing the procedure to score a lead is primarily dependent upon information gathered around the lead's occupation and role in that industry which helps to determine whether they're appropriate to sell to.
  • Additional information that comes into play while deciding whether that lead would be interested in a company's products or services include the lead's activities, demographics, or areas of interest.
  • At a more functional level, some of the aspects that are judged to measure a lead's interest include metrics such as i) which email messages leads respond to; ii) which pages they visit on the company website; iii) how long they visited, iv) any forms they filled or downloaded; v) whether they clicked on a blog post or connected via social media.
  • However, the significance of the metrics depends on whether the company is selling a product or a service and the industry they are selling to.

Sales qualifying lead scoring system or SQL:

  • Once a lead is transferred to sales and is considered to be actionable, sales representatives are required to further scrutinize the lead before assigning it to a dedicated account manager.
  • This process includes a series of conversations in which the Sales Development Representative clarifies the needs of the lead and provides the lead with any supplemental information that they might need to confirm their decision.
  • The types of supplemental information include case studies, ROI calculators, and free trials.

SQL implementation in a US commercial bank :

--By Schermer

  • U.S. Bank is the 5th largest commercial bank in the United States.
  • The company Schermer, as a vendor of the U.S. Bank, established lead scoring criteria for the bank and also groomed the qualified leads using email retargeting and additional thought leadership content.

--By Salesforce

Best practices for a Successful Lead Scoring Model by Salesforce:

As mentioned above, Salesforce played a key role in implementing successful lead scoring models for US Bank.
  • According to Salesforce, using the following best practices, a B2B (not specific to commercial bank) could really help improve sales productivity and the health of the company's sales funnel.
--Using Negative Scoring and Score Degradation:
According to Spear Marketing, 50% of companies could still benefit from putting a scoring reduction model in place.

--Setting up a separate lead scoring model :
It is advisable to set up different scoring models, for separate product lines.

--Model customization based on high-value actions and web pages
Pricing page or contact us pages are considered more high value". As such, these pages should be assigned with higher point values.

--Not to assign points for every opened email:
Assigning points to every opened email often causes inflated lead scores. Therefore, submissions or page views generated from the email are often seen as a more appropriate metric.

Research Strategy:

  • Reports and publications of commercial banks in the US:
To find out how the leading commercial banks are setting up a sales qualifying lead scoring system, we looked into the websites of several reputable commercial banks such as JPMC, US Bank, Bank of America, and Citibank. We wanted to find out whether any of the banks talked about any rules or procedures they follow in order to finalize sales leads. However, presumably owing to the fact that these types of information are part of competitive business strategy for the banks, the information was not publicly available.

  • Reports by vendor companies :
We were able to locate some of the vendor companies that implement predictive analysis technologies for determining SQL scores. These companies included Salesforce, Schermer, DecisionCrm, and Agilecrm. With this we wanted to find whether the companies implemented their systems in any of the big commercial banks. Examples were found for Salesforce and Schermer. However, the implementation did not make a clear distinction between SQL and MQL and used lead scoring as an umbrella term. However, we provided the best practices outlined by Salesforce, even though they were not specific to SQL.
  • Banking federation studies and reports :
We also looked into reports and publications by reputed US federations such as the American Bankers Association, the Savings and Loan Association, and the National Bankers Association. Our aim was to find relevant benchmarking or best practices studies about the SQL scoring system in commercial banks. Unfortunately, we were not able to find any relevant studies related to SQL in commercial banks.

Part
02
of two
Part
02

B2B Sales Lead - Best Practices 2

Use of structured content journey maps, Engaging customers through newsletter emails with content of the newsletter emails created around customer needs rather than product messages, the use of targeted HTML emails, and keeping track of the time taken to respond to each email are 4 additional best practices when setting up a sales qualifying lead scoring system for a commercial bank.

Context

  • A lead's interest is functionally measured while a sales qualifying lead scoring system is developed based on metrics such as buyer personas, firmographics, behavior, interest/intent, and BANT-budget, authority, need, and timeframe.
  • A 2018 B2B banking case study by Odyssiant

  • The use of structured content journey maps was one best practice that converted customers into marketing qualified leads.
  • Engaging customers through newsletter emails, when the content of the newsletter emails was customized to the customer needs rather than the product messages, was one best practice that converted customers into marketing qualified leads.
  • When applied, those specific best practices were able to generate 1,277 new Marketing Qualified Leads.
  • An Indusind Bank case study

  • One proven best practice in B2B banking is the use of targeted HTML emails.
  • An example of a targeted HTML email is the sending of HTML emails to high net worth customers by private banks.
  • The practice of using targeted HTML emails is in conformation with two elements in the lead score determining metrics, namely, the buyer persona and their need.
  • Another proven best practice in B2B banking is keeping track of the time taken to respond to each email.
  • It enables alerting agents of upcoming deadlines and keeps the management team informed about the number of unanswered emails.
  • The practice of keeping track of the time taken to respond to each email enables "delivering customized response and services to customers" and is in conformity with the timeframe metric.

  • Research Strategy:

    As it was already mentioned in the previous request, best practices specific to Sales Qualified Leads were hard to come by. As such, we broadened our scope to include Marketing Qualified Leads, assuming that the best practices for both would overlap. The metrics for determining lead scoring as defined and explained by Technologyadvice.com was used as the base for this research. The metrics consists of factors such as buyer personas, firmographics, behavior, interest/intent, and BANT-budget, authority, need, and timeframe. Using that specific strategy we were able to find two case studies that detailed best practices about MQL: a 2018 B2B banking case study by Odyssiant and an Indusind Bank case study.


    Sources
    Sources

    From Part 01
    Quotes
    • "Lead scoring is a methodology used by sales and marketing departments to determine the worthiness of leads, or potential customers, by attaching values to them based on their behavior relating to their interest in products or services. The "value" of each lead varies from company to company, but generally is characterized by the interest shown in the company or their places in the buying cycle. Companies assign point-based systems in qualifying leads or simply refer to them as "hot," "warm" or "cold" based on the history of interactions"
    • "The first goal of companies is to get sales leads or prospects into their pipeline, but once a substantial number of leads have been obtained, it's important for companies to focus on the prospects that are most interested in buying, which is where lead scoring can play an important role."
    • "Sales teams and marketing departments need to agree on the definition of a qualified lead for the lead scoring process to begin. To score a lead, information is gathered about the lead's occupation and role in that industry to determine whether they're appropriate to sell to. Information about a lead's activities, demographics or areas of interest also come into play when figuring out whether that lead would be interested in a company's products or services"
    • "Metrics that companies use to measure a lead's interest include which email messages leads respond to; which pages they visit on the company website; and how long they visited, any forms they filled out or downloaded or whether they clicked on a blog post or connected via social media. The importance of various metrics can change depending on whether the company is selling a product or service and what industry they are selling into."
    Quotes
    • "Sales Qualified Lead (SQL) The qualification process doesn’t fall entirely on the shoulders of marketing. Once a lead reaches sales and is confirmed actionable, sales reps must further qualify the lead before assigning it to a dedicated account manager. This usually happens through a series of conversations in which the SDR clarifies needs and timeline, and provides the lead with any supplemental information they might need to confirm their decision (case studies, ROI calculators, free trials, etc.). The aim of the SQL stage is to turn the lead into a business opportunity."
    • "If your marketing team delivers leads they think are qualified, but really aren’t (for example, leads that meet your targeting criteria, but don’t have purchase intent), the sales team will inevitably waste a lot of time reaching out to people who aren’t interested and don’t convert. Sales enablement goes out the window, productivity drops, and the sales cycle itself becomes tiringly long."
    • "Take Marketo, for example — one of the biggest marketing automation software vendors in the industry. Marketo only passes about 10 percent of their new names to sales development each month, and about four percent of their existing prospects. But taken cumulatively, this adds up to 2,000 MQLs (marketing qualified leads) every month. Of those MQLs, development reps pass about 7 percent to account managers, and a breathtaking 80 percent of those leads convert into opportunities."
    Quotes
    • "As the 5th largest commercial bank in the country, U.S. Bank had a wealth of untapped insight and expertise. "
    • "We established lead scoring criteria, and nurtured the qualified leads using email retargeting and additional thought leadership content."
    • "Because of our access to real-time analytics and insights, we were able to dynamically and continuously optimize the campaign based on what worked and what didn’t."
    • "Campaign conversion rates improved by nearly 500% during the last month of the campaign, as AB testing and campaign optimization delivered stronger results. In the end, cost per lead improved to roughly $200, well below original expectations. The campaign delivered a pipeline of 1,400+ contacts to US Bank, 115 of which were nurtured, scored and handed over to sales as MQL’s."
    Quotes
    • "US Bank is the the middle of a rapid roll out of Salesforce’s AI-powered Einstein features for its wealth managers to help it convert retail banking customers into its wealth management divisions."
    • "The bank started by rolling out Einstein Discovery lead scoring on top of Sales Cloud to forty teams of wealth managers in three geographies: Minneapolis, Washington and Milwaukee."
    • "This premium feature uses machine learning to score leads by their propensity to buy, or to qualify for wealth management in this case, and rank them for sales staff to optimise their prospecting."
    • "Hoffman says that these teams have seen an average improvement of 2.34x in conversion rate"
    Quotes
    • "Financial services organizations across the globe are embracing predictive analytics at an increasing rate in order to explore new opportunities fine-tune existing programs, minimize risk and improve efficiencies. There are 4 key ways in which analytics-derived predictive insights can enable banks to not only grow their lending business but also make it more profitable. In this document, we investigate how banks can use analytics to improve their targeted marketing activities, helping them acquire the right customers while lowering the acquisition costs."
    • "With a considerable amount of their marketing budget spent on lead generation, lenders are looking to launch their marketing campaigns through the right channels and target the right set of prospects for enhanced business impact. The conversion rates of the generated leads can then be increased by providing a priority list to the sales team."
    • "Combining the lender’s data and additional relevant data with machine learning algorithms; predictive models can be built for scoring the generated leads. Lead scoring aids in identifying quality leads that should be targeted in the order of propensity for accepting a loan."
    • "Applying predictive lead scoring to these credible customers would then help sales team to prioritize the leads. For instance, if the first 10% (or 1st decile as per the lead scores) of the leads are pursued, then the lender can acquire almost two times as many customers as acquired without lead scoring. This takes the conversion rates up north between 40% - 50%. The customers thus acquired, will also improve the profitability of the lending business since the default "
    • "The achieved efficiency would be reflected in their Costs Of Acquisition (CAC), and Customer Lifetime Value (CLV) which are calculated as:"
    Quotes
    • "A few weeks ago, we wrote a post explaining some of the most common scoring and grading scenarios that B2B companies might encounter when setting up a lead qualification model — and how to handle the different combinations of lead scores and grades. Today, we’d like to build upon that discussion by offering up some essential lead scoring best practices. According to a 2015 study by Spear Marketing, 68% of B2B marketers are employing both behavioral and demographic scoring. It’s an encouraging statistic, but as the study further divulged, not all marketers are getting the most out of their lead scoring systems."
    • "Taking your lead scoring model to the next level by employing some of the following best practices can really help improve sales productivity and the health of your sales funnel — not to mention go a long way toward patching up tensions between marketing and sales. Take a look!"
    From Part 02
    Quotes
    • "From these insights, lay out a set of criteria that your sales and marketing teams absolutely must agree on. Your list should include some or all of the following: Buyer Personas: At the most basic level, sales and marketing need to agree on a few ideal customer profiles (ICP) that are prerequisite to lead qualification. These profiles typically address job title/role, key challenges, motivations, and interests. ICPs tell marketers who their audience should be, based on the kind of people sales wants to talk to. Firmographics: Firmographics are all about finding a good fit. Most salespeople look at company size, industry, and geographic location to determine, at a high level, whether or not a lead would be eligible for their services. If the firmographics data doesn’t match your requirements, you should consider discarding the lead (although there can be exceptions here). Behavior: Unlike firmographics, behavioral data is about what’s not stated. Some marketers refer to this as “lead intelligence” or “digital body language (DBL).” With the right tools, you can analyze a lead’s digital behavior and make inferences about their status or position in the funnel. E.g. a prospect downloads a case study, followed by a pricing sheet, so they’re probably a hot lead in the final decision-stage. BANT: BANT (budget, authority, need, timeframe) is an age-old framework for lead qualification first articulated by IBM. This is an important aspect of lead qualification, especially during the sales development process, but businesses should be careful not to get too hung up on matching all four BANT criteria for each lead. Sure, lead quality is just as important as quantity, but if you’re too stringent, you may see an unsustainable drop in lead volume. Interest and Intent: Even if a lead does match all four BANT criteria, or is a perfect “profile fit,” as SiriusDecisions would call it, that doesn’t necessarily mean they’re qualified. What you should really be looking for — perhaps above all else — are interest and intent. I.e. the lead is interested in your brand, and intends to purchase."
    Quotes
    • "Streamlined Lead Management Service Over Multiple Channels Better experience: Talisma CEM keeps track of the time taken to respond to each email query. This information is then used to alert agents of upcoming deadlines, and inform Management (through end-of-day reports) of the number of unanswered emails, if any, classified by type. This also helps in delivering customized response and services to customers."