How to create a predictable sales pipeline (1/2)

How to create a predictable sales pipeline (1/2)

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Do I need a qualification system for my leads?

Well, nowadays there are no problems with traffic, due to the huge number of marketing platforms and instruments. However, it’s all about money. You may have great lead generation campaigns, tons of marketing qualified leads but have an unpredictable pipeline.

Today, we explain the difference between MQL and SQL and some tips on how to convert your MQL into SQL and then into paying customers. You'll be able to raise your pipeline prediction to a new level and decrease your CAC.

We do not dive into your product/service details but highlight common ways how to qualify your leads and finally, improve your closing rate.

Difference between MQL and SQL

Difference between MQL and SQL

First, let’s make a line between Marketing Qualified Leads (MQL) and Sales Qualified Leads (SQL). What’s the difference? Briefly speaking, the main difference that MQL is just curious about your product/service while SQL is ready to move further as they are considering a purchase.

Let’s take a look at a quick example:

Imagine that you are walking within your local mall at a weekend. As MQL you’re probably just browsing. Sure, you may visit some stores (especially, if you see something eye-catching), and it shows your interest, but there’s a little chance that you buy something.

Meantime, if you are walking within your local mall and looking for a gift for a wedding anniversary, you’re walking straight to the required shop, as you have fully emerged need and you’re looking for the best approaches to perform it.

That’s the difference. As a SQL you know what you need and you’re looking for a solution that suits your needs.

Usually, SQL’s are highly interested in making a purchase, they are requesting quotes and live demo sessions.

How to identify your MQL?

Marketing qualified leads. Seriously?

Let’s take a look at how to find out the right MQLs among your website traffic.

Usually, marketers use lead scoring tables to automate the lead qualification process. Here is the scope of criteria you should use to assess your leads:

DEMOGRAPHIC/COMPANY INFORMATION
Choose and rank factors that already represented in your existing customer base (location, company size, industry/domain, and everything else that facilitates your customer identification). Briefly speaking, it represents your ideal customer profile.
ONLINE BEHAVIOR
Define criteria that indicates your lead is more than just an ordinary spectator. There are several triggers that show it: 1. your lead downloaded an ebook/article 2. attended your webinar 3. visited several times pricing page/contact form.
ENGAGEMENT
Assess your lead by his engagement with your social and email campaigns. It should be a combination of opens, clicks, conversions.
Review the MQL definition quarterly, for a better outcome.
If you have several product lines, set up separate scoring models for every product.

After you set up a lead scoring threshold, you'll be able to make a successful lead transition MQL to SQL.

But how to deal with your SQLs, who successfully passed your threshold? Check it out in our next article!


About authors

Ivan Vetrau
Ivan Vetrau
CEO & Founder Invatechs Software
Sergey Kravchenko
Sergey Kravchenko
Senior Partner SIWUS INNOVATION LAB