Successful businesses thrive on data. Whether it’s customer data, machine data, financial data or one of the myriad other data types, businesses that can manage and utilize their data correctly within a CRM have a huge advantage over competitors who do not.
In one of our recent reports, we quizzed organizations globally on how confident they were with their data, where that confidence stemmed from, and what operational benefits they saw as a result of this high-data confidence. The top 8 percent of respondents who had high or very high confidence in their data produced more accurate sales forecasts and achieved higher lead-to-customer conversions.
When data is properly captured and controlled by an organization, and all personnel are invested in maintaining its integrity, the commercial benefits are far reaching.
A lesson in database health for marketing
Flight Centre in Australia is a good example of how good data practices can generate considerable revenue when it comes to marketing. For many years Flight Centre outsourced its digital support to an external agency, and in doing so, had very little control over the application of its data and digital marketing programs. The company’s email program in particular was hindered; with the team challenged by poor visibility into critical insights and performance metrics, which in turn impacted on subscriber engagement and speed to market.
Flight Centre insourced its email program to gain greater visibility and control over its execution, and the metrics supporting it. Implementing a data hygiene strategy from Return Path for Validity to reduce churn and improve overall database hygiene, Flight Centre identified and removed more than one million unengaged or obsolete subscribers from its database, without negatively impacting traffic.
Following this, Flight Centre’s retention rate improved by 480 percent, open rates increased from 19 percent to 25 percent, click through rates grew from 4 percent to 6 percent, and average speed to market went from one day down to less than an hour. And all of this was largely a result of simply applying better data management systems.
Interestingly, these results are similar to those achieved amongst European businesses when GDPR came into force. As large tranches of data had to be purged from programs in the EU to comply with GDPR, European businesses saw better performance. For Flight Centre, however, this was a proactive move rather than one forced upon it.
The link between data quality, adoption and productivity
Unfortunately, the majority of businesses are not leveraging their data so expertly. Forty-two percent of our research participants estimated a loss in revenue ranging from 5 percent to more than 20 percent due to poor quality CRM data. Worryingly, 52 percent responded that they didn’t know because they “can’t measure it, can’t manage it”. It’s not a stretch to suggest they may be losing out on more than 20 percent of revenue. When one takes into account that the average UK medium-sized business does £17m turnover (House of Commons Library figures), just 6 percent of this lost is £1m! This really drives home the impact to the bottom line that poor quality data can have on a business.
What’s important to understand about high quality data and its effective use, is that technology is only one part of the puzzle — people and processes are key to ensuring data is not only high quality, but it’s also utilized to its utmost.
In our recent webinar with Ben “Salesforce Ben” McCarthy and Lucy Mazalon from THE DRIP, we dug into the interrelation between these three elements. Ben discussed the links between data quality, adoption and productivity, and how one begets the next. In many ways it’s a chicken and egg scenario. Data quality is needed for user adoption, as users won't engage with a system if they don’t trust the data. Conversely, the data won’t generate trust if it isn’t timely, accurate and relevant.
Those 8 percent sitting at the top of the tree have cracked the code and are reaping the productivity and profit benefits. What we discovered from the research is that these high performing organizations had three core commonalities, which I’ll detail below.
Strong data governance processes and different regional approaches
Data governance encompasses the people, processes, and technology employed to manage a business’ use of data. As such, it’s important to establish a standard for data that ﬁts the business’ particular needs and processes, as well as a plan for enforcing and supporting that standard.
Becoming data-driven begins with deﬁning what each of these foundational elements mean to the business, and putting a framework in place to ensure their stability. A key goal in data management should be to simplify processes where possible. More process automation means fewer steps end users need to remember, creating less friction and resulting in a more proactive approach to data best practices.
How various businesses decide to construct these processes really comes down to what works best for them. Our own research of our global customers indicates, whilst North America and Europe are closely aligned in terms of their balance between cleansing and maintaining their existing data stores, with discovery of external data more of a sidenote, it’s a slightly different story in APAC, where users are possibly more proactive in terms of data cleansing at point of entry. Both options are equally valid, but perhaps speaks to a younger CRM market in APAC, where legacy data issues are not (yet) as pronounced as for NA/Europe.
Their leadership prioritizes CRM data quality
The support of C-suite leaders in data management projects is instrumental to ensuring their success. If you are trying to engage company leaders in a data management strategy, you need to speak their language when demonstrating the negative impact poor data quality has on the bottom line. My previous analysis that poor data quality could be quite reasonably costing a medium business £1m a year is a good starting point. Extrapolating this to a large UK business that achieves average revenues of £233m (House of Commons Library) and the same equation points to £14m lost!
On a more granular level, our report also shows the impact poor data quality has on sales forecasting and lead conversion. Just over a third (34 percent) of organizations with poor or neutral data quality were able to generate accurate forecasts. In that same organizational group, only 15 percent were satisfied with their lead to customer conversions rate based on their CRM data. When you deliver the data importance message in these kinds of terms, it’s far easier for executives to understand and commit to driving a business-wide effort that prioritizes proper data management.
A cross-functional management team
Strong data governance also requires investment and accountability from representatives across the business. Any department that accesses your CRM data will have different views on how best to use it, and they all need a seat at the table.
A cross-functional management team for data governance and management strategy is key to keeping the project on-track. High performing organizations recognize this, and 29 percent said data quality is the responsibility of a full-time cross-functional team, higher than any other approach, and more than double the respondents whose data quality was poor. By hearing from multiple voices and viewpoints across the business, it’s easier to get the full picture on the life cycle of the data, how it is collected and managed, and identify business risks specific to various departments.
No matter where you operate, a successful modern business is driven by the quality of the data it holds. There is no secret sauce or quick fix that ensures data is high quality and remains so indefinitely, that your employees will use the data to its utmost, or the benefits will be felt fully. Those top 8 percent have combined appropriate technology solutions with a data-first mindset held throughout the organization both horizontally and vertically. For many organizations to achieve the same results it will require a major culture shift, but in reality, these businesses have nothing to lose and everything to gain from getting their data management strategy in order.
Guy Hanson, data expert