Data is everywhere — and that’s good news for businesses. Today, companies handle data at volumes and speeds never seen before, allowing them to achieve higher and higher levels of profitability.
However, one significant problem with this rapid turnover of information still exists — the potential for errors to creep in at the margins. Data errors can cost companies millions on marketing campaigns that deliver few, if any, results.
According to one study, global consumer brands let $50 billion in digital marketing go to waste each year — about half of their collective budgets. Data errors are a significant part of the issue.
Any data, while being collected and afterward, can accumulate errors. For digital marketing purposes, the data in question can encompass:
- Website traffic
- Competitor activities
- Focus group feedback
- Individual page bounce rates
- Search engine keyword usage
- Referring webpages and channels
- Customer and visitor demographics
These data types are incredibly useful beyond marketing. They inform pricing strategies, graphic and web design choices, expansion plans and much more.
Now that you understand the data types involved and the money left on the table, it’s time to dive into lessons on the cost of data errors.
Failing at Productivity
If you want to remain productive during marketing campaigns and succeed in your goals — driving social media shares, improving newsletter signups, increasing website conversions, etc. — you need to stay organized. When it comes to data, disorganization has a huge productivity and monetary price tag attached.
Why? Because errors in data require rework. In marketing and every other business function, revisions are something you can’t afford. Think of the effect on your business when your marketers and strategists lose time reorganizing data, correcting errors or cleaning up databases instead of leveraging what you’ve gathered.
Research concludes data analysts spend as much as 40% of their time validating and vetting data. This considerable amount of time is better spent processing data and strategizing on the future of the company.
Doing away with this type of janitorial work requires a multi-pronged approach, including a culture where everybody values and maintains clean data, reduces the number of databases in operation and engages smart automation tools to look for redundancies and errors.
Damaging Brand Reputation
When communication fails, marketing fails. The result can damage your reputation as a business. Reputation damage extends far beyond the embarrassment of failing to stick the landing on a digital campaign. Data errors also invite catastrophe concerning compliance risks, keeping operational costs low and failing to understand customer engagement and satisfaction fully.
A failure in reputation is a failure in management.
To start, organizations need to take a closer look at how they gather data from the people who matter most — customers. You’ve probably used surveys to see what’s working and what’s not.
However, are you cherry-picking the results you want to see? Are the questions phrased in a way that might cause customers to understate negative feelings in favor of positive responses? Don’t ask leading questions. Instead, solicit honest feedback.
Succeeding in business and maintaining a positive reputation requires intellectual honesty when data is concerned. When it comes to recovering from an already-damaged reputation, companies need to conduct follow-up surveys to see how, if at all, sentiments are changing over time.
Not Visualizing Data
Data isn’t useful if you can’t interact with it. Interaction typically requires finding a way to visualize it. Number-heavy or highly technical data can be hard to understand, which makes it crucial to convert it into an easily digestible format.
Visualization affects reputation, too. If customers can’t make sense of the data you publish, it can get construed as misinformation. When companies or organizations use misleading geometry in their graphics to promote their agenda instead of the truth, people tend to notice.
Think about how much less useful a Google Analytics dashboard would be without clear and intuitive graphics. Website analytics are just the beginning. Data visualization is a powerful tool in nearly every business function, including:
- Tracking company-wide strategies and the reasons behind them
- Optimizing delivery routes and identifying strategically-placed partners
- Discovering how to target users whose profiles match your buyer personas
- Pinpointing areas for sales territory expansions or additional business locations
- Spotting purchasing trends in real-time, including geographical, demographic and regional
Data visualization allows you to break down complex concepts into simple terms your team can understand.
Losing Profits and Opportunities
Errors in numbers can result in a loss of profits. For example, if you sell one of your products too cheaply, you’ll lose revenue without making up for it in market share. A lack of market research and a failure to gather insights into customer spending habits will come back to haunt you.
Choice paralysis is another phenomenon where you might miss out on business opportunities. It results from companies offering similar products at similar price points, a failure to differentiate. If companies don’t gather data on how customers feel about the products, they fail to understand what their target audience wants.
Your company may engage in what’s known as cost-plus pricing. You must gather data on the material, labor and infrastructure cost of offering a product, then add a markup to the final price. Mistakes made here can devastate your bottom line. Cost-plus pricing is a close cousin to value-based pricing, where customers pay more for reasons that are harder to quantify. It’s a function of perceived value and loyalty.
For cost-plus pricing to work, you need highly trustworthy data on your company’s real-world costs of doing business. For value-based pricing to work, you need accurate insights into competitor pricing and market data. Plus, it’s crucial to understand brand loyalty and differences in spending habits based on demographics and geography.
One of the major data types named earlier is customer data. It’s one of the most critical elements of any marketing plan. Measuring the effectiveness of your data in terms of profits lost isn’t the only way to look at a problem. Conversions can take many forms, including newsletter signups, requests for quotes, providing an email address, sharing content on social media and following through on a purchase. Accurate data powers all of it.
The wrong data can sink your conversion rate and send advertising to the wrong audience. For example, if you’re not digging into data on successful referral pages and channels, you’ll likely end up spinning your wheels, placing ads in the wrong channels.
Data that’s essential to targeted advertising includes:
- Abandoned shopping carts: Where in the process customers gave up on their purchase.
- Would-be customers: Data from social media, search engine ads, local mailers, etc.
- Barriers to conversions: Pinpoint bounce rates, conversions and technical problems.
Accurate data and regular reporting are your friends, along with A/B testing. If you can’t find a technical reason why people don’t convert, it might be because the form is too long, the layout of the page is unappealing or the language of your calls-to-action is vague.
Don’t Let Data Cost You Opportunities
A lack of high-quality data can result in missed opportunities to gain new customers and keep existing ones. For small business owners, looking for areas where data-gathering methods fall short and taking measures to eliminate errors is key to survival against larger companies.
It’s also essential for companies with limited funds to ensure they measure the right data. How much money is a Like or Share worth? Don’t get caught up in vanity metrics if your data indicates they don’t yield tangible results. Instead, gather recent, relevant and accurate data that makes it possible to meet your business goals.