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An outdated sales database means the data you collect and maintain offers little value, plus it is having a negative effect on your bottom line.

At best, bad data is costly to maintain and ineffective to use. More importantly, bad data could lead to inaccurate business and marketing decisions that do more harm than good.

With new research below from Oracle, DemandGen, and Experian, here are four signs that you need to update your sales database to optimize performance and productivity.

Ineffective Sales Leads

This infographic is from last year; however, the data from it remains as relevant today – that as much as 40 percent of all B2B sales leads contain bad data. This data results from poor initial entry, missing items, outdated information and duplication.

If your team is not having much success contacting leads, often signalled by a poor lead-to-meeting ratio, outdated data may be a culprit. If you have this issue, perform an audit to examine data entry behaviours as well as verification checkpoints. Refreshing existing contacts and implementing more effective processes moving forward is necessary in this instance.

Infographic-Data-Survey
Detail Credits: http://blog.integrate.com/infographic-dirty-data

Concerning Churn Rates and Satisfaction Ratings

A major purpose of a database is to strengthen your ability to manage relationships with customers. If you experience a significant upturn in customer churn and a significant downturn in satisfaction ratings, bad data is a likely reason.

Armed with incomplete or inaccurate data, sales teams will have trouble with follow-up communication or developing effective relationship strategies. Faulty email addresses would cause a customer to miss out on messages sent through an email marketing system, or you could be targeting the wrong person due to a change in their job function.

Sales people may also have difficulty completing all-important follow-through and follow-up activities that impact satisfaction and retention.

According to Indeed.com, in the US alone, over 50 percent of workers are thinking of changing their jobs in 2016.

It can be extremely difficult to ensure your sales database is consistently accurate. Taking this jobs statistic alone, what sort of impact will that have on your sales database and marketing automation plans?

Poor Marketing Results

Predictive analytics is the use of data for automated reporting and trend identification. Marketing and sales teams rely on analytics to make decisions on which prospects to go after with specific types of communication and messaging strategies.

If your marketing and sales activities are highly inefficient and ineffective, analytics probably aren’t working well either. The common cause is bad or outdated data. Simply put, bad data in, bad data out. If you input bad data you output inaccurate information that is being used in decision-making. Decision making that is having a direct impact on your bottom line.

In DemandGen’s 2016 report “What’s Working in Demand Generation?” lead quality remains one of the top priorities for B2B marketers this year, “as they look for their increased emphasis on data-driven marketing and predictive analytics to yield more qualified leads.”

The main means of driving both early stage (77%) and later stage (85%) leads is Email, with telemarketing coming in at 24% and 42% respectively.

Top Channels For Driving Early-Stage Leads DemandGen Report 20162016 DemanGen Report Lead Generation Contact

Marketing relies on current, accurate data to develop highly targeted campaigns that support sales activities.

A Bad Bottom Line

One of the most tangible and obvious signs of the need for a database refresh is a bad bottom line. Poor revenue and low profits are common financial results when bad data is driving selling activities.

Your salespeople rely on thorough and accurate data to continually improve their selling processes. Data provides a picture of a buyer’s experience throughout the buying cycle. Without current, accurate data, it is harder to monitor sales performance. Thus, it is also hard to coach and develop reps for peak performance. Inevitably, productivity and revenue suffer.

In Oracle’s “The Future of Modern Marketing: 2016” report, a number of global marketers gave their predictions on what would be the hot trends for 2016.

“Sales enablement is the most important marketing function heading into 2016.” Matt Heinz | President, Heinz Marketing Inc

“The most useful measure of marketing automation performance is conversion rate” Jordie Van Rijn | Emailmarketing and eCRM consultant, Emailmonday

“84% of top performing businesses are using or will use marketing automation in 2016. Marketing automation needs leads, and while content is the most potent fuel for lead generation, managing and leveraging that growing library of content will be vital in order to fully utilize marketing automation.” Yoav Schwartz | CEO, Co-Founder, Uberflip

The whole point of marketing – social media marketing, content marketing, inbound marketing, email marketing, video marketing, digital marketing, traditional marketing – is to drive sales. That’s it folks! It’s all about the sales.

And with 84 percent of companies using or planning to use marketing automation to drive the sales and marketing efforts, what happens if the data you are using is inaccurate?

In a 2014 EDQ survey taken by more than 1,200 organisations in the UK, US and Europe, across a range of sectors and company sizes, it was found that inaccurate data has a direct impact on the bottom line of 88% of companies, with the average company losing 12% of its revenue.

According to DatabaseMarketing in an article from February of this year, the latest research carried out by Experian from 1,400 businesses across eight countries, shows that businesses estimate that they could increase sales by almost a third (29%) if customer data was completely accurate.

The same report stated that 75% of the respondents cited email as the most used channel for marketing communications, and of those respondents, 73% can point to a business impact as a result of the inaccuracy.

Conclusion

Bad data leads to ineffective and inefficient business activities and poor bottom line results. If your team’s performance is weak or declining, conduct a thorough audit of your data and your processes for gathering and maintaining data.

Good data is essential to maximising the value of sales leads. Simply pointing your finger at your sales teams may be the wrong option.