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The Why of Data Driven Marketing
Every marketer faces a daily deluge of data and is charged with the task of getting more from ever-expanding volumes of data in order to make all marketing efforts more effective and efficient.
Q: What percent of marketers say data-based decisions are more effective than gut instincts?
A: 67% (How this number isn’t 100% in 2020 is beyond us!)
Q: What percent of companies cite data quality and completeness as the biggest challenge to executing data-driven campaigns?
Q: Why are more than half of companies struggling with data quality?
A: Data Decay
Like tooth decay, data decay not only stinks it leads to rotten campaign results. Did you know that:
- 25-33% of all email addresses become outdated every year
- 25% of data quality problems are caused by user error
- Dirty data costs businesses an estimated $2.5 Trillion per year
Q: What is marketing’s dirtiest secret?
A: Data quality!
When it comes to resolving the issues caused by dirty data, marketers have a lot of questions, including:
- Where do I start with my data?
- How do I solve my data problems?
- Is my segment data quality good or bad?
- Can I personalize content well with the data I have?
- Am I marketing to everyone on my list that I should be marketing to?
Six Metrics for Measuring Data Quality
Before you can ensure your data quality is good, there are six variables you need to measure:
#1 – REACH (a.k.a. Marketability)
Reach is the data needed to market to contacts and accounts across various channels, from email, mobile and phone, to mailing address, social channels, messaging, and more. A couple of questions to ask yourself when considering the reach of your data:
- What percentage of the people in your database can you reach across different channels?
- Are you getting the results you want using the channels you are currently using?
Most businesses are pursuing omni-channel initiatives, but it requires good quality data to execute campaigns with confidence.
#2 – VALIDATION
Validation measures the quality of certain elements of data that can be verified for proper formatting. It is usually performed via a third party vendor. Data that you should validate perpetually includes: email, mobile, phone numbers and mailing address. When it comes to validation, we recommend a two-step process:
1) Use web forms that allow you to collect the data you want
2) Use a third party data vendor to confirm the data you collect is good to go.
Six Reasons Data Validation is Vital to Your Success
- Data is no good if you can’t reach anyone with it.
- Sales teams must have current and correct data in order to engage prospects and close deals.
- Validation directly impacts marketing campaign deliverability.
- Two words: Sender Score. Similar to a credit score, your sender score measures the health of your email program, your reputation as a sender, and how mailbox providers view your IP address.
- Validation helps you avoid spam traps.
- Validation improves the performance of your marketing lists.
#3 – STANDARDIZATION
Standardization evaluates the level at which your data adheres to a standard set of values. Examples of data that benefit from adhering to a standard value: states, provinces, country codes, ZIP and postal codes, job titles, industries, revenue, company size, B2B, B2C, etc.
If you want to develop segments, create targeted lists and use dynamic content based on different elements, it’s important to have the data standardized – otherwise it is next to impossible to scale personalized campaigns.
Standardized data helps you create and successfully execute more targeted communications and personalized emails. It also helps you reach smaller and more segmented audiences, which is essential to your account based marketing (ABM) strategy. The more targeted your message is, the better the results you are going to see – and all of this requires standardized data to achieve.
#4 – TOTAL ADDRESSABLE MARKET (a.k.a. Total Market and Look-Alike Modeling)
TAM refers to the available universe of contacts and accounts that match your target audience. TAM leverages segment data and compares it with 3rd party data sources to ensure you are reaching everyone you should and could. You need to know how your segment data compares to what’s available in your TAM if you want to grow your business and expand your market reach.
#5 – ENRICHMENT
Enrichment is the ability to provide data elements that are beyond what is captured through traditional methods. Often these data elements go beyond basic contact information and surface-level interactions, and are items that you may not typically ask for. A few examples include: intent data from ABM vendors, predictive scoring and household information.
#6 – COMPLETENESS
Completeness measures the percentage of data in key fields that can be used to drive segmentation and personalization. One reason why you may want to collect additional data such as job titles, industry, annual revenue, state, province, country, language, etc. is so you can get a more complete picture of your customer. In short, it is essential to have complete data in order to glean the kind of customer insights that lead to a more productive and profitable segmentation strategy.
Three Ways to Improve Data Quality
Improving your data quality is as simple as establishing checks and balances for the three primary stages in your data’s life cycle: inbound, ongoing and outbound.
As inbound data travels into your marketing database and CRM systems, you need mechanisms to catch bad data and improve data quality. These include measures such as:
- Basic form validation – i.e. Make sure prospects are filling out all the fields you want
- API-enhanced form validation – Use a third party to validate, append and enrich data
- Data orchestration processes – Too many manual uploads lead to input errors and other data issues. Manual processes require thorough post-upload quality checks.
Once data is in your system it will decay over time. Ask yourself what measures you have in place to ensure quality is maintained. Tools you will want to use often to ensure data quality is good include:
- Marketing Automation Platforms (MAPs)
- Customer Data Platforms (CDPs)
- Third Party integration workflows
- Standardized business processes that perform different aspects of data quality
As you prepare to use your data, ask yourself what checks and balances you have in place to ensure it is ready for use. Quality should always be assessed as data is being prepared for an outbound campaign. We recommend getting in the habit of conducting a segment level analysis of your data quality prior to sending a campaign because of the impact it has on:
- Campaign performance – High quality data leads to high-performance campaigns
- Personalization – Current, correct and complete info is essential to ABM
- TAM – Knowing the actual size of the segment you are targeting is a game-changer
Sureshot’s Approach: Take Command of Your Data
Many marketers struggle with data visibility when it comes to the six metrics for measuring data quality. Command empowers marketers to know their data quality, marketability (reach), field completeness and TAM in real-time. In addition to equipping you with instant insights into the six metrics, it also identifies and fixes critical data issues in campaign segments before you launch them — nice.
How does Command work?
Command integrates seamlessly with your MAP (Eloqua, HubSpot, Marketo, Salesforce, etc.). Command continuously analyzes and improves the quality of your data at every stage in its cycle. With improved data quality you have the confidence of knowing that every time you activate a channel or campaign, you are going to get the maximum return possible for your marketing efforts.
What features does Command offer?
- Out-of-the-box integration to MAP contacts, companies and lists
- Real-time email and phone validation
- TAM data from Zoominfo
- Shareable data trends and scoring metrics