Data Cleansing Checklist
We know how important data is to maximizing efficiency and reducing waste at every point of operations – or at least we should. But not all data is good data. On average, across the industry, it takes 143 attempts to create one successful lead. While a 143:1 ratio seems bad enough already, that number is even more startling when you realize what industry-leading companies are managing.
The best companies when it comes to data management have a lead-to-conversion ratio of 68:1. They achieve this through top of the line data hygiene. How impactful can this level of data management be?
Well, it means they need half the number of leads for every successful sale. That can either mean half the budget for the same results or twice the results on your existing budget.
Now, employing good data hygiene practices doesn’t guarantee this. What it does do is put you in a position where every dollar you invest goes to the leads that are most likely to turn into customers, and even loyal, recurring customers. That’s because “clean”” data accounts for the nuances that can suck up a marketing budget without being of real value.
So how do you effectively clean your data and ensure that you’re only generating high-quality leads in the future??
Data cleansing checklist
Clean up your data regularly
The best thing you can do for your company’s data hygiene isn’t to clean it – it’s to clean it regularly. Data is a fluid stream of information, which means it’s constantly changing with each new input. Setting up periodic data screens is the best way to stay on top of evolving data.
Depending on the size of the data sets you’re working with, you may need to clean it quarterly, monthly, weekly or even daily in certain circumstances. However often you do it, be consistent. Make room for spontaneous checks as well, such as when you receive a huge influx of new data after a marketing campaign.
Define high-quality data
Without knowing what high-quality data looks like, it’s impossible to filter out “bad data.” The quality of a data set is always defined by how useful it is to the people handling it. Whether you need that data for market analysts, campaign managers or sales reps, understand the goals of the people using the data.
Bad data often leads to dead ends, like contacting leads with out-of-date contact information or sending a welcome email to someone who has already made a transaction. These are examples of data that lead to resource wastage, which should be eliminated at every possible point.
Search for inactivity
An inactive lead is a bad lead. That’s not because the person has done anything wrong. A bad lead is just someone who is unlikely to get to the sales point. This could be because they’re no longer interested in your product, they’ve found a competitor, or communication just broke down.
One of the most common examples of a bad lead is an inactive account. This is a lead that doesn’t engage with the marketing material you send them for one reason or another. It’s okay to let these leads go – it’s even advisable. By removing them from your contact list (one of the most common databases), you make space for active and engaged leads.
Remember, we’re dealing with the lead-to-conversion ratio here. So it’s not about how many people you engage with – it’s about how many of those engagements are likely to end in a sale.
Have you ever tried to create a new account on a website you forgot you already had an account for? That little ‘error’ message that tells you that your current email address is already in use is a big part of data hygiene. Nope, that’s not just to prevent bots.
That error message stops people from creating duplicate accounts and clogging up a company’s data set. Duplicate accounts are a hazard for an obvious reason. If someone isn’t interested in your product, they definitely don’t want to hear about it twice. Even when dealing with a solid, high-quality lead – why would you want to spend twice the resources sending them the same message?
Duplicate accounts are especially costly on email lists. Most email marketing platforms will let you manage a certain number of emails on your list before they start charging you for the higher packages. MailChimp, for example, lets you manage a mailing list of up to 2000 addresses for free. That’s a monthly service you don’t have to pay for until your list is big enough to afford it – but only if that list is full of high-quality leads.
Use opt-in checkpoints
So you’ve been running your marketing campaigns for a while, and you’ve got a long list of leads to follow up with. Some of those leads came in through last week’s campaign; others have been around since last year’s campaign. What if those who have been on your contact list for months haven’t made a transaction and show no indication of doing so in the near future?
An opt-in email can be sent to any lead in your contact lists. All it does is ask them if they would like to continue receiving communications from your company. If they don’t, they can unsubscribe directly from the email.
But how does losing a lead benefit you? Well, what you’re actually losing is someone who was never going to buy anything, to begin with. More importantly, allowing people to opt—inputs the decision in their hands, meaning you spend fewer resources on data hygiene and get a more accurate return of who is interested and who isn’t.
Clean up your input channels
The quickest way to get bad data is through human error in the input section. If someone misspells their email address or phone number, then you can’t reach them, regardless of how interested they are in your brand or product.
In this regard, high-quality data starts with verifying the contact information leads volunteers at the input stage
Data hygiene is about creating efficiency by removing information that leads to poor business decisions. Don’t neglect it as both a marketing and risk management strategy. It could be the difference in projecting next quarter’s success story.
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Data Cleansing Checklist for Leads – Any great marketing or lead nurturing campaign starts with solid research and the freshest highly targeted lists. Impact Enterprise’s highly skilled data specialists can get the data, cost effectively and efficiently. Test pilots are always FREE. Services include, lead validation, data enrichment, contact research, data entry & CRM hygiene; content services include content management, influencer mapping and moderation for social media; AI Data Annotation services include image labelling, language processing and geospatial analysis.
Impact Enterprises was Established in 2013 and recruits skilled talent from bright young professionals in Zambia, Africa, where 59% of graduates find themselves unemployed and without an opportunity to showcase their skills and dedication. For recurring projects, the company provides a dedicated team to oversee operations for each client and guarantees an exceptional standard of delivery.