Mind the gap: the impact of poor data on sales, and what you can do about it
Marketing and sales teams rely heavily on quality prospect data in order to effectively progress leads through a sales cycle. But what happens when that data becomes out of date and forgotten? It can seriously impact on an organisation’s conversion rates, and it can also cost serious cash to correct.
A new study conducted by SiriusDecisions found that between 10% and 25% of customer and prospect data held in marketing databases contained serious errors. Inaccuracies ranged from incorrect demographics to a complete lack of disposition detail. Among the organisations studied, those deemed as being stronger than average displayed smaller amounts of database errors (10%). Typical organisations scored 25% for the volume of unhealthy data.
The shift, according to the report, has to be from one-time data cleansing activities toward implementing continuous data improvement processes. This is important to guarantee future data quality, ensure the organisation’s sales cycle is optimised at every stage and, most importantly, save the organisation from spending over the odds on critical data repairs.
What can you do to improve data collection?
To further demonstrate the business impact of poorly managed data systems, the study looks at common stages of a typical sales cycle and observes process corrections that can be made in order to ensure validity of data throughout the cycle, whilst maximising conversions.
- Enquiry to Marketing Qualified lead stage
At this point in the cycle, leads need to be verified at source before they hit a database. This aids better lead scoring early on in the cycle. What’s more, correctly validated and scored leads provided to the sales team at this stage have a 25% higher chance of converting later on, according to the report.
- Marketing to Sales Accepted lead stage
At this stage in the cycle, it’s common that two databases are in use, one for marketing and one for sales. It’s advised that where this is the case, a layer of “virtual unification” is required to join both systems and ensure that leads are being transferred from disparate systems without errors.
- Sales Accepted to Sales Qualified lead stage
Clean quality data is needed at every stage, but this is deemed the most vital according to SiriusDecisions. At this stage a sales team needs to be able to effectively communicate with leads, targeting them with relevant solutions and incentives. And where a marketing team may work with sales on data based initiatives, they must work in unison to ensure data integrity and compliance with CRM systems.
- Sales Qualified to Close lead stage
Understanding lead disposition is essential at this stage in order to successfully close a deal which is why this, and other later stages of the sales cycle focus heavily on data integrity. The report suggests that appointing a primary CRM system which houses account data is essential and will act as the go-to system for other systems to pass data to, for example from marketing automation systems.
The report outlines the impact on conversion rates and revenue when cohesive data processes are implemented. They predict that by maximising conversion rates at each stage of the sales cycle, strong organisations could yield a 66% increase in new business revenue.
Quick data capture tips
- Enforce spelling and naming conventions
Some fields in your database will require standard entries most of the time. For example country and job title will remain fairly fixed but spelling mistakes could prevent you from reporting properly on your database. Consider implementing drop down lists or naming conventions for abbreviations to ensure consistency in your data entries.
- Dedupe records
Duplicate records can cause problems when it comes to managing a smooth sales cycle. Therefore cross checking your database for duplicate records and merging them will ensure contact information is up-to-date and ready for the sales team to act upon.
- Implement a validation process
The first stage in the SiriusDecisions data collection process suggests that validating email addresses at source is a good way of improving lead scoring processes. However this doesn’t have to be done entirely manually. You could add an email verification step into your form submission process which prompts users to double check their email address entry before they submit and before that record hits your database.
The crux of the report identifies that a best-in-class data strategy doesn’t fall solely on one team. Both sales and marketing, and to an extent IT, have a business obligation to ensure that each stage of the sales cycle is optimised to garner quality data from a range of databases and avoid wasted sales and marketing efforts.