Lead Conversion Analysis

We begin by checking the data. We export leads from your CRM or sheet for a chosen period, usually the last three to twelve months, with fields for created date, source, service, owner, stage history, outcome, value and loss reason. We look for gaps: missing sources, leads with no owner, stage changes without dates and duplicates. We clean what can be cleaned and note what cannot. Next we define the funnel with you, for example enquiry, contacted, qualified, proposal, won. We calculate the count at each stage, then the conversion rate from one stage to the next and from the start to the end. The result usually shows one or two stages where the drop is much larger than expected, which are the best places to work. We measure timing. Many businesses discover that leads contacted within an hour convert far better than those contacted next day, or that proposals sent after three days are rarely accepted. We calculate median time to first contact, time from contact to proposal and total sales cycle length, and compare them against win rates. We then segment. By source: which channels bring leads that become customers, and at what revenue per lead? By service: which services convert and which need better qualification? By location or branch. By owner: do some salespeople follow different practices worth sharing? By lead type: form, call, WhatsApp or referral. We compare ad cost with outcomes where cost data exists, so you can see cost per customer and not just cost per lead; see cost per lead and cost per acquisition reporting and lead quality and sales outcome analysis. We study lost deals through reasons recorded in the CRM and, with your permission, a short sample of notes or follow-up calls. We look for patterns, such as price objections after a vague first call. We also check the leads that were never worked at all. We present findings in a clear report: a one-page summary, charts of the funnel and timing, tables by source and owner, and a ranked list of recommended changes, each with the evidence behind it. Typical recommendations include faster first reply rules, a shorter qualifying form, a script for a common objection, dropping a poor source, shifting budget to a better one or adding a follow-up step. We estimate the effect where the data allows, labelled as an estimate. We can build a repeating dashboard so you track the same measures monthly; see lead generation dashboards. We cannot analyse data that was never recorded, and conclusions from small samples stay tentative, but even a simple review often shows where the largest gains are.