Guest Blog: Why Data Is More Valuable Than Gold

Guest Blog: Why Data Is More Valuable Than Gold

This week we have something a little different. Our friends at DataCaptive have kindly provided some special guest content. And if it’s one thing these guys know and know well, it’s capturing data!
This week they’re reminding us why ‘data is valued more than gold’ and ‘quality is the key’.

Businesses cannot survive without their customers. The sole purposes of companies that are formed are to sell their services to their targeted customers. It has been like that from the beginning of organized trade.

Sales & Marketing which evolved as we know today has its base which is deep rooted in customer acquisition. Knowing your customer can sometimes win half the sales for you. The history of business tells us about tradesmen who have been keeping up to date information regarding their clients & prospective buyers. Coming to the modern world there’s no doubt that customer data is one of the most valuable assets a B2B organization has access to. Without accurate information regarding the target audience, it’s impossible to market, sell & provide good customer service. Data quality in B2B is one of the real problems that companies face simply because data decays so rapidly.

Whether companies realize it or not the efficiency, productivity & drive of their B2B marketing & sales team is directly dependent on the quality of your data. Data has become significantly important in the world of business today. Poor data quality has the chances of affecting a range of aspects including lead generation, sales opportunities, finance, customer relationships etc. Good data leads to less time spent on prospecting, more customers & ultimately more revenue. The impact of low-quality data can range from lost accounts to catastrophic revenue loss.

How to know if data is bad?

Imagine that a particular set of B2B contact & company data is available with a certain company A. They have been having that particular set of data for quite some time. Now the time has arisen & one of the sales reps of Company A has accessed the data set & tried to use it for his sales purposes. But while checking the data he notices that it’s inaccurate.

There are missing fields like email ids in the case of some clients while in some others the phone number is missing. In certain accounts, the data is entered into the wrong field & there are duplicate entries in other accounts. Misspellings, typos & spelling variations are prominent throughout the data & it hasn’t been normalized. All these can constitute for bad data which can drive any sales rep crazy. These are all examples of what can constitute to be bad data. Earlier we discussed how to identify the data decay & the methods to ensure data quality. If you haven’t read that post, you can do so here: How To Detect B2b Contact Data Decay & Ensure Data Quality.

Now let’s see in which all ways bad B2B marketing data affects the marketing performance of B2B companies.


Effect Of Bad Data On Marketing:

Misleading Conversion Insights & Reduced Optimization Potency 

Attaining information in a timely manner is really essential in the cut throat world of corporate. But when data isn’t up to par, marketers won’t be able to make informed decisions based on lead data which in turn prevents good leads from getting converted through the pipeline. 

Annoyed Customers & Prospects 

Imagine a marketing specialist is one of your clients & he has been promoted to a senior manager or director position. It might rub him in the wrong way if you continue to send emails addressed as ‘marketing specialist’. The same can go for names for example Mr. John won’t be pleased for continually receiving emails that are addressed for Mr. Jon. You might be unknowingly be making these mistakes all the time if you’re marketing database isn’t accurate or up-to-date. 

Pipeline Becoming Slow 

It’s important to make contact with prospective customers at the apt time for making sales. Without proper data governance software, there’s no other option for organizations other than manually catching & correcting thousands of prospect data errors. Now the real problem that happens is that this manual data cleansing slows down the rate at which leads move through the pipeline, which results in good prospect data going bad.

High Churn Rates 

Churn rate is the percentage of email subscribers that leave your list over a period of time. About 25-33% of email addresses become outdated every year. So, it shouldn’t be a surprise for marketers if list churn depletes about 25-30% of average email list every year. Because of this your subscribers won’t be seeing your emails anymore because they will be going to spam, they don’t check that particular email address or they just stopped opening your messages. 

Decreased ROI from CRM & Marketing Automation 

The ROI for marketing tech systems takes a great hit by wasting of the usage volume on ineffective data. About 36% of B2B marketers say that “insufficient data quality” is the biggest obstacle to success in marketing automation success. It’s being said that the failed email & address validation issues would translate into more than $2.5 million wasted on media spend with average B2B lead prices at over $50. 

The Solution:

In the modern corporate marketing world where data is valued more than gold, quality is the key. But marketers are finding it increasingly difficult to stay on top of data hygiene. The solution can be leaving the task of one-time data cleansing to the experts & shifting to on-going data maintenance.

As your valuable prospects & customers change contact information & jobs it’s critical for you to keep up with them. Database maintenance should be integrated into the day to day activities of the life of marketers. This is because the impact of bad B2B marketing data can be disastrous to your marketing efforts & it doesn’t have to be in that way. 

Also, check out their blog on how the quality of B2B data can be improved with Data Appending – Boost B2b Contact Data Quality With Data Appending.


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See you next week,


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