The problem I want to solve :
Ignition’s sales team lacks of rigor when using our CRM : the data is not clean at all, and there are lots of missing data. So the CRM doesn’t allow us (for the moment) to lead insighful analysis about our customers and sales.
Moreover we have 2 main tools to run our business : this CRM + an internal back office which contains all the matching and candidates data. We never managed to merge both of them to conduct cross-analysis.
Objective :
- cleaning CRM Deals & Data from BO.
I could also lead an analysis on Companies or Contacts but I will lack of time to clean all these datasets, I prefered focusing on cross-tools, which is a major pain for our teams
- cross data analysis between our CRM and our internal matching tool
→ Seasonality ? Turnover per client ? Net profit per client ? Average basket ? Repeat Business ?
→ understand factors driving sales at Ignition : customers’ drivers
→ top 20% customers (top = 1% // Large = 4% // Medium = 15%) + factors driving sales for these clients ?
→ top time wasters (the clients who are taking up most of our time but aren’t vital for our business → do we paddle them away ?)
→ typical customer : what is the typology of clients with whom we work better ?
→ Churn rate (when and why do they leave) ? How to retain customers at ignition ? Customer lifetime value ? (comparing between loyal and broken relationships)
→ what are the improvement factors of our MER/Placement ratio ? (went down from 9% to 5%)
→ for one job, how many pitchs / MER / offers fo we need on one job to optimize our chance to close the job ?
→ what is the ratio candidates / opportunities on each type of job ? what is the closing duration ?
→ are we better on new or repeat jobs ?
→ what is the conversion rate between pitch and mer per sales (not coach) ? per teams ?
→ how many jobs do we need to open per month to reach our objectives ?
- build a model to predict the amount on our recruitment business