• Skip to main content
  • Skip to secondary menu
  • Skip to primary sidebar
  • Skip to footer
  • Articles
  • News
  • Events
  • Advertize
  • Jobs
  • Courses
  • Contact
  • (0)
  • LoginRegister
    • Facebook
    • LinkedIn
    • RSS
      Articles
      News
      Events
      Job Posts
    • Twitter
Datafloq

Datafloq

Data and Technology Insights

  • Categories
    • Big Data
    • Blockchain
    • Cloud
    • Internet Of Things
    • Metaverse
    • Robotics
    • Cybersecurity
    • Startups
    • Strategy
    • Technical
  • Big Data
  • Blockchain
  • Cloud
  • Metaverse
  • Internet Of Things
  • Robotics
  • Cybersecurity
  • Startups
  • Strategy
  • Technical

Three Ways to Successfully Manage Your Marketing Data

Larisa Bedgood / 5 min read.
August 27, 2016
Datafloq AI Score
×

Datafloq AI Score: 82.67

Datafloq enables anyone to contribute articles, but we value high-quality content. This means that we do not accept SEO link building content, spammy articles, clickbait, articles written by bots and especially not misinformation. Therefore, we have developed an AI, built using multiple built open-source and proprietary tools to instantly define whether an article is written by a human or a bot and determine the level of bias, objectivity, whether it is fact-based or not, sentiment and overall quality.

Articles published on Datafloq need to have a minimum AI score of 60% and we provide this graph to give more detailed information on how we rate this article. Please note that this is a work in progress and if you have any suggestions, feel free to contact us.

floq.to/lgLJV

Data is at the center of todays marketing strategies essential to driving the right connections with the right people and across the right channels. With the fluidity of data moving in and out of channel systems and consumers interacting with brands through any number of touchpoints, data is constantly changing. Marketers must be extra diligent to proactively manage customer and prospect data to maintain the integrity of such a valuable business asset.

Research firm Ascend2 recently conducted a survey examining the state of marketing data management.

Study findings included:

Measuring ROI to attribute sales resulting from the marketing data management investment is a top priority. Improving the quality and accessibility of marketing data are also top goals.

Marketing Data Strategy Goals

Companies fail or thrive based in large part on the quality of their business decisions. Making more accurate decisions is the most valuable benefit of using marketing data for 54% of companies.

Decision-marketing-data

Poor access to marketing data will limit its use. And if the marketing data is of poor quality, it will have limited usefulness. Combined, these are the most significant barriers to success.

Marketing data management barriers

Tactically, the most effective use of marketing data is for campaign targeting. Getting the right message to the right person at the right time requires quality, segmented data.

Effective Use Data

Here are three key strategies to successfully managing your marketing data as an asset:

One: Break Down the Siloes

Data siloes continue to be one of the biggest challenges that enterprises face when it comes to customer data. Data may be stored in various departments or different systems handle different sets of data, such as billing, shipping, and customer service records. These disparate systems of data prevent a unified customer view which impedes optimal marketing, sales, and operational performance.

How difficult is the challenge of siloed data? Many of the clients we work with have numerous systems of information. We integrated 7 systems of data for a regional furniture retailer and over 25 sources for a large manufacturer. And the larger the company, the more systems that must be created to handle growing volumes of information. As an example, the average hospital system maintains 100+ unique siloes of provider-related data.

Additional research by Teradata supports Ascend2s finding:


Interested in what the future will bring? Download our 2023 Technology Trends eBook for free.

Consent

  • Nearly 50% of marketers think data is their companys most underutilized asset
  • 96% of marketers believe data siloes prevent a holistic view of campaigns
  • Less than 10% of marketers use their data in a systematic way
  • Only 18% of marketers have a single integrated view of customers

Two: Implement Ongoing Data Integration and Data Quality Measures

64% of companies outsource all or part of their marketing data management. In many cases, companies do not have all of the skills required or the rapidly evolving technology in-house.

Manage marketing data

A data management provider will perform the following functions to ensure important customer details are integrated and remain current.

Data Identification:

An important first step is to identify all sources of data, fields of interest, format standards and definitions. Multiple sources of information may be used to contribute to the marketing database. These sources may include POS, e-commerce, customer loyalty programs, billing systems, and any other source of information that contains important customer details.

Data Cleansing & Standardization:

No data is perfect. Different and sometimes conflicting pieces of information can be found across multiple sources for the same contact or company. One-time feeds such as trade show data or prospect list purchases quickly age, and incoming data sources may lack critical data elements. The goal is to rely on the data being as accurate as possible. For example, ZIP codes can be corrected if city and state are correct, centuries can be inferred for dates, and area codes can be added where missing.

Each data type must also have the same kind of content and format. Consistent formats need to be identified for data elements such as equipment identifies, phone numbers, dates, etc. A data quality solution should contain built-in transformation routines that assist in this significant process according to your companys requirements.

Cross Referencing:

Duplicate data is the top data quality problem for 30% of organizations. Cross referencing, or matching, is the checking of two or more units of data for common characteristics. The matching process removes data duplications and further improves data accuracy.

For example, names and addresses are often the identifying field for a data source, particularly customer data. However, this data can become inaccurate and deteriorate over time, or the data may have been incorrectly entered at the beginning. Performing matching to identify and correct these errors will discover intelligent links among customer profiles to merge duplicate records.

Data Enhancement:

Records are often missing important details. Data enhancement adds additional insight into contact details, demographics, lifestyle interests, and firmographics.

By following this 5-step approach, a company can achieve a single source of truth through consolidation of all cross referenced data and elimination of redundant information. Business rules should be applied to reconcile conflicting characteristics and maintain constant identifiers over time.

Three: Establish Business Processes to Ensure Data Quality is Continually Maintained

Business processes should also be established to ensure data manually entered into systems is of the highest quality possible. Many organizations experience data errors when information is manually entered, at a rate of 2% and 8%. Even one wrong number entered incorrectly can cause a payment to fail, a wrong part number to be shipped, or a host of other inefficiencies and lost opportunities.

Marketing Data

Data validation controls can be integrated into online forms, using rules to check the validity of data sets. For example, a web form may require a visitor to enter data in specified formats. Or an IRS form may utilize controls to check that positive numbers are being entered into fields. As prospects and customers engage with you online, perhaps filling out an online form, this information can quickly be tested, corrected, and entered into a marketing system through real-time web verification services. Training employees to be more aware of the importance of data quality is also a crucial step to achieving a company-wide awareness of maintaining high quality information.

Data is no longer a commodity that can be taken for granted, but the real value is only equal to the quality and accuracy of the data being used. Implementing a strategy to proactively manage this valuable asset will ensure you maintain a huge competitive advantage now and in the future.

Categories: Strategy
Tags: Big Data, Data integration, data quality, data silos, data-driven marketing, marketing

About Larisa Bedgood

As an omnichannel data powerhouse, V12 Data combines rich data assets with robust technology to provide brands with a seamless and connected customer view. Our solutions bridge the right data across channels to power right time omnichannel engagement when, where, and how a brands' customers prefer. Our data and technology platform links customer records with our proprietary blend of online, offline and digital marketing data for highly personalized, one-to-one consumer marketing, regardless of device or channel.

As a motivated marketing professional, I successfully develop and implement demand generation initiatives and market brand awareness strategies. I have a deep understanding of today's data-driven marketing environment, and have developed my skill-set to support customer relationship-building, content marketing techniques, and inbound and outbound marketing methods.

www.v12data.com

Primary Sidebar

E-mail Newsletter

Sign up to receive email updates daily and to hear what's going on with us!

Publish
AN Article
Submit
a press release
List
AN Event
Create
A Job Post
Host your website with Managed WordPress for $1.00/mo with GoDaddy!

Related Articles

The Advantages of IT Staff Augmentation Over Traditional Hiring

May 4, 2023 By Mukesh Ram

The State of Digital Asset Management in 2023

May 3, 2023 By pimcoremkt

Test Data Management – Implementation Challenges and Tools Available

May 1, 2023 By yash.mehta262

Related Jobs

  • Software Engineer | South Yorkshire, GB - February 07, 2023
  • Software Engineer with C# .net Investment House | London, GB - February 07, 2023
  • Senior Java Developer | London, GB - February 07, 2023
  • Software Engineer – Growing Digital Media Company | London, GB - February 07, 2023
  • LBG Returners – Senior Data Analyst | Chester Moor, GB - February 07, 2023
More Jobs

Tags

AI Amazon analysis analytics app application Artificial Intelligence BI Big Data business China Cloud Companies company costs crypto customers Data design development digital environment experience future Google+ government information learning machine learning market mobile Musk news Other public research sales security share social social media software strategy technology twitter

Related Events

  • 6th Middle East Banking AI & Analytics Summit 2023 | Riyadh, Saudi Arabia - May 10, 2023
  • Data Science Salon NYC: AI & Machine Learning in Finance & Technology | The Theater Center - December 7, 2022
  • Big Data LDN 2023 | Olympia London - September 20, 2023
More events

Related Online Courses

  • Oracle Cloud Data Management Foundations Workshop
  • Data Science at Scale
  • Statistics with Python
More courses

Footer


Datafloq is the one-stop source for big data, blockchain and artificial intelligence. We offer information, insights and opportunities to drive innovation with emerging technologies.

  • Facebook
  • LinkedIn
  • RSS
  • Twitter

Recent

  • 5 Reasons Why Modern Data Integration Gives You a Competitive Advantage
  • 5 Most Common Database Structures for Small Businesses
  • 6 Ways to Reduce IT Costs Through Observability
  • How is Big Data Analytics Used in Business? These 5 Use Cases Share Valuable Insights
  • How Realistic Are Self-Driving Cars?

Search

Tags

AI Amazon analysis analytics app application Artificial Intelligence BI Big Data business China Cloud Companies company costs crypto customers Data design development digital environment experience future Google+ government information learning machine learning market mobile Musk news Other public research sales security share social social media software strategy technology twitter

Copyright © 2023 Datafloq
HTML Sitemap| Privacy| Terms| Cookies

  • Facebook
  • Twitter
  • LinkedIn
  • WhatsApp

In order to optimize the website and to continuously improve Datafloq, we use cookies. For more information click here.

Dear visitor,
Thank you for visiting Datafloq. If you find our content interesting, please subscribe to our weekly newsletter:

Did you know that you can publish job posts for free on Datafloq? You can start immediately and find the best candidates for free! Click here to get started.

Not Now Subscribe

Thanks for visiting Datafloq
If you enjoyed our content on emerging technologies, why not subscribe to our weekly newsletter to receive the latest news straight into your mailbox?

Subscribe

No thanks

Privacy Overview

This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.

Necessary Cookies

Strictly Necessary Cookie should be enabled at all times so that we can save your preferences for cookie settings.

If you disable this cookie, we will not be able to save your preferences. This means that every time you visit this website you will need to enable or disable cookies again.

Marketing cookies

This website uses Google Analytics to collect anonymous information such as the number of visitors to the site, and the most popular pages.

Keeping this cookie enabled helps us to improve our website.

Please enable Strictly Necessary Cookies first so that we can save your preferences!