How Startups can Avoid Potential Failure by Using Clean Data
Startup businesses often fail. The most common reason for failure is cash flow problems, followed by marketing challenges[1]. According to Harvard Business School, even with a windfall of venture-backed capital, five percent of all new startups still fail[2]. eCommerce startups have the highest chances of failure, with 90 percent failing in the first four months[3]. “Inability to compete in the marketplace is a common reason for startup failures,” said Sky Cassidy of data intelligence leader, MountainTop Data. “On the positive side,” Cassidy adds, “it’s worth pointing out that clean data is one of the most important weapons a startup can have in their arsenal, as it can help identify a wider audience of qualified prospects and thus secure more customers.”
The “clean data” Cassidy refers to is a company’s database of names, phone numbers and physical or email addresses of all their current customers and potential prospects. The more a startup engages in data-driven marketing the better their chance of success. Considering that data lists naturally decay at a rate of about 30 percent per year, it is advised that a startup, as well as an existing business, attain their lists and have them cleaned by a reputable company[4].
How much revenue is lost because of inaccurate marketing lists? According to recent estimates, dirty data—data that is incomplete, outdated, or contains errors—costs U.S. companies anywhere from $2.5 to $3.1 trillion annually[5]. Because of the hidden influence of dirty lists within a company, administrators and executives are often not aware that “dirty data” is the reason for lower revenues and lost sales.
If a startup begins their operation with a dirty data, poorly constructed data, or worse yet, no data, they are more likely to become a startup “failed business” statistic.
The alignment of sales and marketing departments is crucial for the success of any business, and is best achieved through accurate, clean marketing data.
Four reasons starting with clean data will improve chances for long-lasting success:
- 62 percent of organizations rely on marketing and prospect data in which up to 40 percent is commonly inaccurate which hurts sales.
- 25 percent of the average B2B database is inaccurate, creating a “leaky bucket” where potential leads escape never to be sold a product or service.
- 64 percent of “very successful” data-driven marketers say improving data quality is the most challenging obstacle to achieving success.
- Marketers can generate 209 percent more revenue when they are well-aligned with their sales department[6]
For many companies, managing and cleaning data inhouse has been a neglected function. Less than half (46 percent) of sales professionals use tools to automatically enrich, append, clean or de-dupe leads before they are entered into databases. Without dedicated systems or outside venders in place, dirty data is bound to spread like wildfire[7].
Sky Cassidy concurs, “Data intelligence is the life force of a business. When sales and marketing professionals are drowning in depths of dirty data, they are handcuffed from making informed data-driven decisions that will make sales and increase their bottom line.”
