Exactly How Bad is Bad Data for You? Step-by-Step Tips to Delete Bad Data

Bad data is detrimental for any marketing program. Even worse, bad data that ranges from duplicate data, incorrect data, broken links, missing files, corrupt files, outdated and invalid data exceed the limit and burden the database and marketing budget.

According to an estimate by Sirius Decisions reveal that organizations spend about $100 for data maintenance in their database, including those bad data records. Approximately, 20% data are inaccurate with 100,000 records in a database which cost about $2M of the marketing budget. In addition to marketing costs and oversized occupancy, bad data affects a brand in many other ways – unnecessary software expenses, poor marketing performance, system slow down, and inaccurate segmentation and personalization are just a few to mention.

Bad Data hinders marketing performance

One of the areas where bad data badly affects performance is low click-through rates and engagement with the audience. Bad health of your database will deter your marketing results and degrade them below the industry standards if your marketing campaigns are based on a range of prospects who might not need your products or offerings. Also, if your data set comprises invalid data, then bounce rates will increase and your campaigns will suffer from poor email delivery and negative reputation. Thus, overall performance and results of marketing campaigns will take a downturn due to bad data range.

Bad Data increases software costs

Do you often see this message pop up in Marketo, or other platforms, stating “You are over your data limit”? If you do, then blame it on bad data which is causing your platform to exceed data space allocated to your package. You may use some SAAS platforms for diverse marketing programs and campaigns including marketing automation, CRMs, ABM, and any other which charge you based on the data range. And as the number of records and campaigns grow, requirement for a larger database increases. At that, with 20-30% of the data set containing poor data, your company is spending more on those software subscriptions than is required.

Bad Data Leads to Poor Segmentation/Personalization

Are you running your marketing segmentation and personalizing your campaigns based on poor data? Then, your campaigns are doomed to failure as your segmentation data may contain inaccurate, duplicate, outdated or invalid data which will hinder delivery of personalized experience. Thus, your campaign is performing no better than a generalized campaign.

Slow Marketo performance due to bad data

All marketing and CRM software platforms perform at its peak in the first six months. Later, these platforms start slowing down with consistent use and data addition and alteration. Each of these platforms are used for updating records, syncing data, segmenting data, creating and running campaigns, measurement and optimization and other marketing activities. And each of these activities takes power and results in addition to additional records with every campaign. Thus, the bigger your database swells, the longer your SaaS platforms take to process data and activities, leaving your system less efficient.

For example if your Salesforce platform is working with as large as one million sized database, small changes made on records will impact the entire database and all data will automate a data sync with the Marketo platform to complete the data update process. Thus, your software platform will experience sluggish performance issues.

If your bad data is ruining the results and eating up hundreds of dollars from your marketing budget, then here is what you need to know. Check out the following step-by-step instructions to delete or trash bad data to prevent loss of performance, resources and effectiveness of your Marketo campaigns.

Each step will require you to define the criteria, evaluate and identify processes, and carry out the cleanse to flush out the data.

Step 1: De-duplicate the data

Duplicate data is one major type of bad data you need to focus on – hence, first things first, you need to spot all the duplicate records in your database. If you are using Marketo, then you get a one-time offer to de-duplicate the database. Though Marketo may not let you de-duplicate the data multiple times, it lets you spot duplicate records.

To identify and access duplicate records, you need to create a Smartlist which will detect multiple duplicate records which contain the same email or other contact details. Two types of records can be duplicates within Marketo, which are leads and contact details. To prevent duplicate records in Marketo, you need to choose API or Marketo forms. Another way to prevent duplicate data is by syncing all Marketo leads with the salesforce platform, searching for leads in SFDC by first name or email address and then updating the data. You can also import all lists in Marketo by selecting ‘Normal.’

Step 2: Get rid of records which do not have email addresses

Your Marketo platform may contain some records that are devoid of email addresses. Since you cannot send them emails, you cannot include them in your campaigns. Hence, those records are unnecessary data that you need to purge from your database to prevent the likelihood of duplicates.

In SFDC, lead records that do not have email addresses are not marketable and thus, get removed after 30 days. However, contact records need complex analysis. For example, if you have an account payable contact that does not have an email address, the address cannot be deleted since the address can be used for billing. Some records you may need to remove from Marketo, but need to retain in Salesforce in order to lessen the risk of removing data crucial for the sales team, but not for marketing activities.  If you want to delete records from Marketo, but retain them in Salesforce, then you need to set the criteria in Salesforce so that that data will not get synced with Marketo unless an email address is available with those records.

Step 3: Eliminate recently removed Salesforce data

By default, records that are deleted from Salesforce do not get deleted from Marketo automatically. To remove deleted SFDC records, you need to create a campaign in Marketo which will run and detect deleted Salesforce records and will purge on spot regularly.

Users can also set up automated batch campaigns to cleanse data and repeat the process weekly. You may keep the process monthly in case you need to trace some deletion occurence in Salesforce.

Step 4: Get rid of disqualified data

In this step, Marketo users need to detect disqualified data and eliminate them to maintain good data health. For this, you need to set up a process that will identify if the disqualified data is bad data.

You can set custom criteria to avoid the risks of deleting recycled records that were mistakenly marked as ‘Disqualified’. You can also choose to delete disqualified data based on reasons of disqualification.

Step 5: Delete hard bounce data

Many marketers choose to delete contact data when the email bounces on that email address – should you? For certain reasons, you may not. Some records that had bounced you may want to retain for reporting purposes. You may need to send those addresses a few more emails to extract data from bounced emails. One way of deleting bad bounced data is to delete data when the ‘Email Invalid’ turns true.

Step 6: Get rid of Inactive records after reactivation campaigns

That’s true, marketers should not delete data if a contact has stopped activities with your emails. There are many ways you can run reactivation campaigns to encourage response and engage with  your correspondence, content, offers or products. After multiple reactivation campaigns, you need to determine the following: if those contacts are inactive over the span of 15 or more months; if you don’t find any opportunities for activities; if those inactive records are Salesforce leads only; if those records are no longer part of any lifecycle stage. You need to perform this as a one-time process to delete inactive data once you have set the criteria. You can also run this process quarterly or yearly to remove and repeat the process to get rid of inactive data as per the set criteria.

If you need to delete bad data and maintain good health of your database in Marketo by using professional assistance, you can discuss strategy with our Marketo certified experts (408) 502-6765. Check out more tips, tricks and updates on our social pages LinkedIn, Twitter (@ShowMeLeads) and Facebook. Keep in touch with our leaders Madhu Gulati on LinkedIn and Twitter (@mgulati) and Prash Shenoy on LinkedIn and Twitter (@shenoyprash) to get in know of the latest Marketo and ABM updates.

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5 Ways Timely Data Health Check Redoubles Your Marketing Performance and ROI

Periodic data health check is an essential practice to ensure clean data for better targeting, engagement and conversion. Here, we will discuss how to audit data and best practices to follow for data cleansing in order to maintain the quality and accuracy of data and thus, improve your campaign performance, conversion and ROI.

If your lead contact database contains a considerable number of outdated, invalid, incomplete and duplicate records, then, chances are that your lead scoring could be inaccurate and you may be spending more than you need to thanks to such poor data health. Poor data health will lead your campaigns to unsuitable or wrong contact details – as a result, your marketing campaigns will try to engage people who might not be interested in your product, service or offers, or who might report your emails and content as spam.

We’ve identified five ways that clean data can help your marketing performance and your marketing ROI:

Clean data helps in better Lead Scoring and Predictive Analytics

Predictive analytics tools enable businesses to distinguish the ideal audience and accounts they need to focus on. Recently, marketers take into account more data points than job titles, in order to take a deep dive into their prospects. The more details they get, they more accurately they can score customers and map them into the right nurturing plan – and the better they get to know their buying behavior and buying intentions. Thus, marketers need to keep incorporating into their database an extensive range of fields which will help them to perform better lead scoring.

Clean data aids in buyers-driven campaigns

Accurate and clean contact dataset benefits marketers with intelligent information that lets them segment contacts based on prospects’ engagement and intentions. The better marketers can segment, classify, and personalize, the more effectively they can target their prospects and lead them through the buying phase. In that way, businesses can achieve better engagement and deliver more personalized content and experience and run lesser risks of unsubscription.

Clean data enables better optimization

Periodic data cleansing and data health check maintenance routine, businesses can ready database for scheduling, scoring and nurturing using their marketing automation platform more efficiently. Apart from that, marketers, users or business owners gain accurate insights and better reporting functionalities.

Clean data boosts performance

Once bad, duplicate, inaccurate or null data is eliminated with a data cleansing process, marketers can focus on completing incomplete data and incorporating with up-to-date. Thus, it is only clean contact records which will enable them to align the right information and content with the right contacts who would be interested and engaged with the communications. In other words, if your marketing campaigns are failing to target or to catch the pulse of the audience, despite relevant and useful content being communicated, it is time to do a data health check and data cleansing.

Enhanced account based marketing

After you have scored your leads, identified them as high-value prospects and want to put them nurturing program – you need to delve deeper on high-value customers to bridge all the communication gaps and feed them with the right information, tips, guides, updates and resources at the right time. Deep account-based marketing needs coordination between sales, marketing and customer service team and updating data collected on accounts from each end of ABM operations. When data collected from all the teams are incorporated, updated and modified in the database, marketers can take well-informed actions and strategies in pursuing key accounts.

Do you find this information useful? If you are interested in going to the next step and get tips on data cleansing and improve data accuracy – read our next blog post on how to do your own data cleansing and health check.