An hour of work of a good seller or marketer is expensive. That’s why it’s necessary to measure to what extent the method in which you acquire clients is effective, and draw conclusions as to where it is worth improving. This will save you a lot of your people’s expensive, wasted man-hours, just because at the right time you have noticed that something is not working. Leads conversion, leads velocity, and lost reasons is a necessary minimum, which we described here. In this article, you’ll learn how to help yourself get to the right conclusions based on data and their appropriate addressing.

Fundamentals of Analytics

Does taking care of data quality in CRM pay off?

Entering additional data into CRM is largely an administrative activity that, to put it mildly, doesn’t excite salespeople. That’s why, the data entered must be analyzed, and we should draw conclusions from it, which will allow salespeople to work more effectively.

15 minutes a day needed to enter relevant data into the CRM (resulting from the proper leads qualification), during each of about 65 business days this quarter would take a total of 975 minutes, or just over 16 hours.

Let’s assume that in Q3 you sent 15 offers to companies where your contact person was not a decision-maker. The conversation with each of them took about 30 minutes, and it took another hour to prepare for the interview, make an appointment, and send a summary. That is 22.5 hours of traders’ work. This is also the time of specialists from the Product / Customer Service department. Let’s assume that 1 offer is one hour of work, so in total, the service of these companies required 37.5 hours (almost one working week).

If, ultimately, of these 15 companies, only one became a customer (conversion at the level of 6%), is it very likely that leads processing, in which we do not have the opportunity to talk with a decision-maker, does not pay off? Of course, the final decision depends on the work-hour rate, and specific numbers may vary depending on the particular company and industry.

However, 15 minutes a day invested in the proper CRM conduct can translate into knowledge about what marketing and sales activities should be avoided. It’s very likely that after one quarter there will probably be more than one conclusion. Unfortunately, in everyday work, we often stumble upon a situation in which customers want to start measuring sales only from the moment they have “above XYZ” leads. The problem is that they are wasting a few months of building good habits and collecting the right data.

Conduct CRM properly and collect the necessary data

The element necessary to draw conclusions based on data is collecting it, which means a well-configured CRM, thanks to which you will be able to answer the following questions within a few minutes:

– for what reasons did we lose potential customers in the previous week / month / quarter?

– what part of the started sales opportunities reached the next stages of the sales process?

– at what stage do we lose the most sales opportunities?

– how many days do sales opportunities spend on average in particular stages?

– how many sales opportunities in a particular week / month / quarter reached the particular stage?

If you are unable to answer each of them, then it means it’s worth improving CRM, because you are losing some valuable knowledge about your sales, and this is usually associated with the fact that your employees cannot work as effectively as if they would, if you managed the company based on relevant data.

Measure the quality of leads

It is possible that a significant part of your sales is based on a specific group of companies – that is, for example, customers from a specific range of industries and countries. That’s why it’s worth measuring the quality of leads that your salespeople are working with. By gathering information about the industry, country, size, type of a decision-maker (and other factors described in this article), you give your company a chance to focus on those leads that most frequently become customers, the sales cycle in their case is the shortest, or cooperation with them is the most profitable – that is, to achieve the desired effects with less work.

How to draw conclusions based on data?

Assign the owner to specific indicators

Let’s suppose you want to analyze how many sales opportunities in a particular week / month / quarter reached the individual stages: a lead was obtained, a lead was qualified, an offer was sent and a contract was sent.

October, week 3. 1 week left until the end of the month.

Leads gained: 12

Qualified leads: 8

Offer has been sent: 7

Contract has been sent: 2

Let’s also assume that the 8 qualified leads this week are 2 times more than the average. It’s worth letting the indicator owner (a specific seller) analyze whether the higher number of leads qualified this week is the result of a specific action that can be repeated and scaled, eg. a properly composed Ads campaign. For example, if the same metric is going to be 1 in the following week, then the owner cannot say “I did not have any influence on my team generating few good outbound leads”. Of course, nobody controls reality 100%, but rejecting the responsibility is the most effective way to stagnate and lack progress. Asking “what can we do to make the X number higher?” will help generate the necessary insights and focus the activities in the right direction.

Analyze data in the context of a designated objective

Below are the numbers describing how many leads in total reached a particular stage from the first to the third week of October. The goals set for the whole of October are given in brackets. It is worth presenting the level of a goal achievement in comparison with the information about how much time has been left until the end of the discussed period – it will help systematically assess how effectively progress is made.

October, week 3. 1 week left until the end of the month.

Leads gained: 33 (45)

Qualified leads: 22 (35)

Offer has been sent: 14 (25)

Contract has been sent: 7 (15)

It is worth analyzing achieved results in the context of a previously designated objective. In one week the results may be lower than expected and in the next one relatively high. Emotions arising in the moment of alternate successes and disappointments may disturb the proper interpretation of reality. Especially that we attach more importance to the opinion of “loudest shouting salesmen”, demanding leads or companies that have not been our clients, “but we talked so nicely, so their objections are the most important.”

If, for example, the sales department before the last week of October has not yet issued half of the contracts planned for this month and sent fewer offers than expected, then most likely the revenue from the new business will be lower than the one projected in the plan. Objective numbers will also help tone up the optimism caused by “several leads – known brands that have come to us”. It’s great, of course, if your company succeeds in getting the attention of well-known firms. Mind you, it cannot justify the failure to achieve the goal that you previously considered the most important.

Look for extremes, regularities, recurrences, and inconsistencies

Systematic review of the most important metrics is the basis for analyzing sales. Usually answering questions asked at the beginning of the article doesn’t take much time (if you have properly configured CRM and earnestly enter data into it), but sometimes looking at the data will require more effort and use of advanced filters / exporting data to Excel. Yes, analyzing numbers may not be the most exciting task, but when it’s needed to increase sales, it’s worth doing – important and necessary things are often not exciting, they may also take time. Especially, if 3 additional hours spent in Excel can help you eliminate dozens of hours spent quarterly, for example, on processing wrong leads or making and correcting recurring mistakes.

When analyzing data, your attention should be drawn by extremes, regularities, recurrences, and inconsistencies. When you notice them, it’s worth checking them out.


“In week X, we have generated an exceptionally high number of outbound leads.”

– is it the effect of a well-chosen target group?

– is this the effect of properly written e-mail content?

– can the actions be repeated and scaled?


“If we fail to collect the information needed to qualify the lead within the first two days from making contact, in the vast majority of cases, this opportunity is lost”

  • do the feelings of salespeople confirm this conclusion?
  • on how many examples are we able to check whether the lack of information needed on day 3 actually meant a lack of cooperation?


“Seller X for a second month in a row sent fewer contracts than the average of a team”

  • did they receive lower quality leads in this period than the rest of the team?
  • has their motivation for work decreased during the indicated period?
  • did they start to make repeated mistakes?


“In the first stages of the sales process, the companies obtained using the form on the website give up further conversations, as the reason giving – this is not a good time to talk about it”

  • are we dealing with inbound leads quickly enough?
  • is this inconsistency repeated in particular industries or in the case of particular people?
  • are we sufficiently enough communicating the value which our solution can bring to the company?

Be open to ideas

If you are just starting to analyze data on marketing and sales, it’s very important to build an atmosphere that facilitates generating ideas and accepting any mistakes (because at the beginning most ideas fail). These initiatives must be defended against perfectionists. Note – some people may be discouraged by the fact that due to the conclusions from the data, you will start doing something “differently than before”, so be prepared for the arguments “but so far we’ve been doing it in the way X, after all Y may not work” . Yes, there is a risk that unproven activities may not work, but this argument can kill any new initiative in B2B marketing and sales – so you should not use it.

In openness to new ideas, it will help explain to all interested parties that there are no “uncontested, always effective truths” (especially in marketing and sales). There are tactics you need to test to know if and when they will work for you. For example, if using cold mailing, you successfully reached the startup industry, it is very possible that in the case of the public sector a completely different marketing channel will turn out to be the right one.

Choose priorities

In a well-configured CRM, there will be a lot of data for analysis, so it is worth your efforts to be focused on what is most important. Therefore, focus on 1-2 metrics, the improvement of which will have the greatest impact on revenues. For example, if at the moment you have a problem with the number of high-quality leads, then take into account this indicator in the priorities. In a situation where you have a lot of valuable leads, but salespeople arrange fewer meetings, it’s worth working on what to do so that more sales opportunities reach the stage of an appointment. And if you do not know what you should focus on – make your prerogative analytics reaching the level that allows you to answer the question about priorities.

Drawing the right conclusions about customer acquisition requires analysis and openness. Avoid assuming in advance that something works, does not work, or is good for your company, because it is different than all others, or not good because . . . it is different than all others. After some time, the effort put into the analysis will pay off in drawing conclusions systematically, as well as in eliminating unnecessary marketing and sales activities.