Fixing Your Data
BY STEVEN WAGNER
5 Reasons VP Sales Should Care
VP Sales Operations has a careful mix of coaching, sales, systems and recruitment in the mix of your daily and annual goals. At the end of the day making quota is the real goal. To have some oversight into the pipeline and activities your CRM is vital to making forecasts and observing your teams progress.
Trouble with CRM’s is they can quickly become full of out of date and inaccurate contact data. With nearly 35% of the data becoming old or obsolete. For your teams they lose time finding and fixing this data.
Nearly 52% of companies only find out the data is bad by an employee. Typically someone in sales. By asking your salespeople to verify data either because of their activities or through chance discovery you cutting into already small amount of selling time.
In our research we’ve found that average sales rep takes 12-15 minutes depending on their tools to fix bad data in a CRM. This time is spent, finding and verifying the data, researching the point of contact, finding data or their replacement, updating the crm and then contacting the new person.
Do this over a week and you can easily lose 2.5 hours.
Ok but out data vendors supply the data, so they can fix it for us?
We’ve seen that most (well-known) data providers can have 5-20% bad data per month, so even then your reps are contacting the wrong person and spending more time finding the new person. Over a three month period of time 15% of the new data is already bad again.
So what can be done to boost accuracy in your CRM?
- do it more than once a year
- have multiple data sources
- work of a born on data – check on
- prioritize accounts – higher priority = more verification cycles
Scenario #1 Established Database – sales rep time with bad data
Lets say your CRM has 100,000 contacts in that your team is prospecting and developing pipeline from.
Now within one year 35% of those contact’s data will go bad. If your company is like most, (54% of companies to be specific) rely on your reps to “discover” the issues.
- 35,000 leads/contact
- Manual process 12-15 minutes
- Data vendor “fixes” ~ 20% bad (7,000 contacts)
- No regular testing of data will have your current lists slip back into bad data
Scenario #2 Rep is prospecting from Data provider + list fatigue
Buy list(s) 10,000
20% bad 2,000
Decays at 3% 300 each month
In 6 months (sales cycles) 1,800
3,800 already bad
20% bad fit = 1,240 opt out
4,960 “leads to work”
Takes rep from 10 months of prospecting at 1,000 per month down to 4~5 months
How to fix:
- Go from manual to automated
- Centralize data under a single point person/director
- Implement data management tools
- Implement tools consistently across all teams (lead gen, mkg, sales, billing)
- Hire talented staff to maintain and create actionable insights
- Be proactive and anticipate data challenges
Data quality in your CRM can be improved and will impact your ability to generate revenue. With ever more tools to prospecting, nurturing and closing sales all relying on your CRM its vital the data becomes accurate and reliable.
The time and investment in CRM data quality improvement has immediate impact to the bottom line. Don’t let bad data cost your team and customers.
Still stuck? How can we help?