A senior analyst at Forrester claims 70% of marketers know their organizations have bad or poor-quality prospect data. Marketers can try to increase their marketing ROI by refining their strategies or introducing technology, but all these efforts are in vain if the data these activities depend on is not clean.
How do you know that a lead is marketing or sales-qualified? Can you use the data from the lead’s conversion journey for lead scoring and attribution? Is your data reliable enough to use for planning effective marketing strategies? All of this is only possible with clean data, and that is where the challenge begins.
Data comes from multiple sources. As data comes in, every entry is treated as a new object (or lead) in your marketing database. This can cause your database to be inaccurate, incomplete, invalid, or inconsistent. To fix this issue, implement a data cleansing solution to standardize and clean your marketing database records.
Data cleansing is a necessary step before you can feed data to any marketing process such as lead sourcing, email marketing, or lead scoring and attribution.
The Data Cleansing Workflow
Before we move on to discuss the impact of clean data on marketing ROI, let’s take a look at the data cleansing workflow and the activities this process involves.
Generate data profiles
Performing a complete profile analysis of quality across all data sources generates a data profile. This will help you to understand how clean your data is and highlight all potential cleansing opportunities.
Data profiles should be generated in the beginning and at the end of the cleansing process. You can compare both profiles to assess how useful the data cleansing process was and if there is any remaining work that can be done to increase data quality.
Perform data standardization
This is where you need to introduce vertical consistency within your database. This includes ensuring all data within a field is valid, consistent, and follows a standardized pattern. Examples of standardization include:
- Correcting misspellings and variations
- Standardizing date formats
- Filling blank values with appropriate data
- Removing data fields that are not necessary to be captured
- Ensuring all email addresses and phone numbers follow valid patterns
Remove duplicates from your data records
This is one of the most crucial steps of the data cleansing process as it ensures uniqueness of your data records and horizontal consistency of your database. If your database does not have any unique identifiers, then you need to implement complex data matching algorithms for phonetic, numeric, fuzzy, or other domain-specific matching. Once you have identified the matches, you can then decide to merge or purge your data records to attain the golden record that represents a single source of truth for the entire organization.
Review you address data
Track bounced emails and undeliverable mailings to assess the correctness of your contacts database. You can also use out-of-the-box address verification modules to check for missing our outdated information. They will help you to parse and understand your address data and see if there is any missing or inaccurate information that can be updated.
3 Ways Good Data Impacts Your Marketing Efforts
Clean and accurate data can drastically increase your marketing ROI. Here are the top three ways in which good data quality helps in your marketing efforts:
1. Plan better lead scoring and attribution
How do you know whether a lead is marketing and sales qualified and not just a dead contact? You can’t base these decisions on gut instinct or experience, you need factual data to understand the relevancy of each lead to your product or service offering.
Accurate and reliable data allows you to design effective lead scoring and attribution models that tell you a lead’s behavior across all digital touchpoints (including links clicked, terms searched, resource downloaded, emails read, etc.).
Imagine having data that does not tell the real story, or tells it in parts or duplicates. Your entire lead scoring and attribution model becomes unreliable. And before you know it, the entire marketing and sales teams invest their efforts on contacts that have no purchase intent.
2. Know who to target and how
With a better lead scoring and attribution model, you can have the top contacts/prospects for your team. Usually called the golden record, this contains top prospects for outreaching whose data is cleaned, accurate, deduped and standardized. Including this, your clean and high-quality data will also give you insights into how to reach them and which digital channels are the most likely to convert from.
This approach will allow you to send more personalized and accurate emails. Otherwise, you’ll be sending emails to prospects that have no relevance with the email content whatsoever. The more personalized your email content, the higher the probability of converting the prospect into a customer.
3. Increase operational efficiency
Cleaning data is the most effective way of resource, cost and workforce utilization. You cannot afford to have your teams spend entire marketing campaigns on false leads. It’s important to mention here that many projects consume entire teams in the data cleansing process. This means that if your team does not have an efficient way of cleaning their data, they might be spending 80% of their time on preparing data for marketing. This is an unacceptable time consumption.
To fix this, it is important to make the data cleansing process efficient and repeatable. The best option here is to choose a self-service, automated data cleansing tool that acts as a central data cleansing hub for all your data preparation activities.
Data cleansing is a crucial process for extracting maximum value from your marketing efforts. It gives your team confidence in their data and processes. Every small decision and workflow can be related back to some factual data. So, save billions in marketing while increasing your marketing ROI by ten-fold with clean data.