SQL: Measurements and Best Practice

Let’s talk SQLs, or Sales Qualified Leads…

SQL: a definition

Once a lead has been qualified by the marketing team and has become an MQL, the sales team become the accountable factor.

Using the information gathered by the marketing team, often added to a CRM, sales must also then confirm a prospect’s needs to find out if they are indeed interested in your product / service and possibly ready to buy.

This stage is very different from qualifying a prospect as an MQL in terms of the timeframe involved: sales teams can often gain a better understanding of a prospect’s needs with a short phone call.

As a result of this call, an MQL can either be judged to be of interest but not yet ready to buy and become part of a lead nurturing programme or be qualified as an SQL to continue their buyer journey.

An SQL is therefore a prospect whose needs and behaviour have been assessed by the marketing and sales teams and who has been identified as a sales opportunity.?

They then move into the sales process intended to guide them up until they purchase your product or sign up for your service.

What does an SQL actually look like??

It is the sales team’s job to qualify a lead as being an SQL.

Some leads can be so “hot” they skip the lead generation stage (or generation of marketing qualified leads) altogether and run straight into the open arms of salespeople. For example, this can happen when your company has been recommended to them by one of your existing customers.

There are some strong signs that let you know when an MQL is ready to be passed on to sales. It’s important to know what these signs are to be able to move your prospect to the next stage as quickly as possible.?

·?????The prospect has a clearly identified need: they visit your website and read your content. This sign is invaluable for salespeople who can adjust their sales pitch accordingly.

·?????The prospect not only views content, they interact with you: they ask questions in a webinar, comment on your social network posts, download a white paper, and request more information.

·?????The prospect views a lot of sales-related content or which is targeted to the “decision-making” stage: if you have already produced and identified specific content to help your prospects take the plunge (e.g. case studies, requests for a demonstration), pay particular attention to prospects who view it. This prospect is obviously very interested

·?????The prospect moves quickly: they view a lot of content in a short period and haven’t wasted time getting straight to the point. They might have already made a decision and want to talk to you. It’s time to give them a call!

If a prospect has shown all these signs, they are ready to be passed to the sales team for a call to qualify them as an SQL as soon as possible.

The key is then to ensure that marketing and sales share a handover process (set out in a Service Level Agreement or SLA) and that there is effective communication between the two.?

Some thoughts:

·?????What information do sales really require?

·?????How can marketing transmit this ahead of time?

·?????Is your CRM configured correctly?

·?????Is your marketing teams’ tools able to reduce sticking points and to automate the transfer of information?

It’s important to have answered all of these questions before passing prospects to the sales team so that they are not left to decide on their own when to qualify a prospect as an SQL.

Defining SQL

Exactly how you define an SQL and the criteria for this depends on your specific business. In most instances the “BANT” criteria offers the best definition:

Budget: they have a budget to spend and which will enable them to meet their aspirations

Authority: they can make a decision about your product / service or can make the case for it.

Need: they have a clearly defined need and the sales team can position themselves to help solve their particular problem

Time frame: the prospect knows when they want to implement this solution and has incorporated this into their timetable.

Converting an MQL into an SQL: what to monitor?

It’s easy to calculate the conversion rate from an MQL to an SQL:?

(Number of SQLs / Number of MQLs)

= Conversion rate

It’s important to calculate your conversion rate from MQL to SQL and to monitor it closely, because it will depend very much on the strategies that you have put in place. It can also give you an indication of when is the best time to pass an MQL to the sales team.

However, the length of your sales cycle can also have an influence on your conversion rate. If this is long, compare the SQLs generated at the end of your average sales cycle with the MQLs generated at the beginning of the cycle.

For example, if your average sales cycle is 6 months, your calculation would look like this:

(Number of SQLs in month 6 / Number of MQLs generated in month 1)

= Conversion rate

Furthermore, the move from an MQL to an SQL should be made as quickly as possible. If this takes too long, it means you haven’t done a sufficiently good job earlier on of qualifying an MQL or haven’t identified that they weren’t ready to be qualified as an SQL.

Use indicators like the conversion rate to further adjust and refine your processes as you go along.?

A good conversion rate is not necessarily a high one

Having a high conversion rate from MQL to SQL is great. But if it’s too high, it could mean that your criteria for qualifying a prospect as an MQL are too strict, and that you are possibly missing good targets for lead nurturing.

A very low conversion rate should set alarm bells ringing: you might be qualifying prospects as MQLs too quickly, and, depending on your business, may need to review some of your criteria for doing so.?

So, using an average MQL to SQL conversion rate of 13%, employee or customer recommendations have an average conversion rate of 24.7%, while an emailing campaign has an average rate of just 0.9%.

These stats do not mean you scrap email marketing, but rather that you exercise caution when assessing your conversion rate.

Questions to ask include:

?·?????Where do most of your SQLs come from?

·?????What is your strong point?

·?????In what areas could you improve?

Monitor your conversion rate without comparing it too much with others.

Just as your definition of an SQL will be unique to you, the conversion rate can very much depend on your B2B business.