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4 Tips to Better Gauge the ROI of Your Custom Targeted Database

4 Tips to Better Gauge the ROI of Your Custom Targeted Database

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In a previous post, we took a look at five key metrics to gauge your list’s performance and effectiveness. But we left out one crucial KPI that you should always be keeping track of: the ROI that your list generates. As we’ll see below, measuring exactly how much return a Custom Targeted Database brings to the table can become a little challenging. That’s why we’re setting aside this entire entry to help you get started with this critical marketing yardstick.

It’s typically hard to correctly determine the ROI of most custom target lists since they’re mostly used for top-of-funnel activities. This means that, by the time a lead becomes a customer, the touch points associated with the contact list that contributed to the sale are often difficult to trace since they took place at earlier stages in the process.

To get around this, the following tips can help you reliably measure how much revenue your custom targeted database helped generate:

 

  1. Know exactly where contacts come from.

In order to accurately gauge ROI, you need to find out where every contact that becomes part of your list originated from. Did a lead come from organic sources? Which paid source did a particular database record pass through before entering your funnel?

For your custom targeted database, this means having separate fields that report where and how you got the contact information.

 

  1. Refine your sales funnel stages.

There’s a surprising statistic from MarketingSherpa being thrown around that claims 68% of marketers haven’t yet identified their sales funnel. If you happen to be part of this group, you need to define and refine the stages in your sales funnel right now.

What are the steps a prospect goes through before being deemed sales-ready? What actions constitute a conversion in each of these steps?

 

  1. Track and score leads throughout your funnel.

Once you’ve established the precise steps that a prospect has to go through in order to turn into an opportunity, you now need to assign points that indicate how sales-qualified that particular lead is.

This is called lead scoring and is a crucial component of accurately measuring marketing ROI. Points are assigned based on the lead’s attributes (demographic and firmographic details) and their actions (interest and intent).

 

  1. Match closed deals with past touch points.

Now that you’ve got contact source information and lead scores recorded in your custom targeted database, it’s time to take a look at the data for deal closes. These closes should be tied back to the series of touch points that preceded the deal.

Marketingprofs says there are four categories of closes based on source and nurture history. It’s important that you identify the right classification for a particular deal, so that credit and attribution can be correctly given.

You can now start reliably measuring the ROI of custom target lists with these four tips in mind. The main idea is that your custom targeted database does contribute to the revenues your marketing and sales processes generate, provided that you’re using it correctly in your campaigns.

5 Metrics to Measure the Health of Your B2B Contact List

B2B Contact List

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You can’t manage what you don’t measure. That’s according to an old business adage that’s still relevant in marketing today, especially now that marketers are drowning in an ocean of metrics and KPIs that let them know what works and what doesn’t. So what numbers should you be keeping track of to get a feel for how your B2B contact list is performing?

As you may know all too well already, everything in B2B marketing starts with your list. That’s why you need to keep this critical campaign component firing on all four cylinders. To find out whether your B2B contact leads database is really up to the task, here are the five key metrics you should always be monitoring:

 

  1. Inbox Placement Rates and Delivery Rates

Inbox placement rates (IPRs) and delivery rates are two distinct metrics that measure email deliverability, although they’re often incorrectly used interchangeably. Delivery rates count the number of emails sent that didn’t bounce, while IPRs only consider emails that actually made it into the recipients’ inbox.

These two numbers can indicate the overall health of your B2B contact list. Low IPRs and delivery rates are often taken as signs that a list probably needs some scrubbing and updating. Recent research from Return Path reports that average global inbox placement rates hover around 80%.

 

  1. Hard Bounces

Bounce rates refer to the percentage of total emails that were not delivered. Soft bounces happen when emails get rejected from the recipient’s server because of a full inbox. Hard bounces, on the other hand, take place when emails are not delivered because of invalid email addresses.

You want to keep an eye on hard bounce rates, since ISPs and mail providers view high levels of hard bounces as a sign of spammy behavior. To help minimize hard bounces, regularly scrub your B2B contact list for invalid or non-existent email addresses.

 

  1. Unengaged Subscribers

Unengaged subscribers are inactive contacts in your list that have yet to promptly opt out. These are subscribers who remain on your B2B contact leads database but haven’t opened or responded to your emails in a while.

Sending emails to unengaged subscribers can harm email deliverability, since doing this tends to trigger spam alerts in most ISPs. So, manage inactive subscribers with a reengagement campaign or by removing them from your B2B contact list altogether.

 

  1. List Churn Rate

List churn rate or attrition rate is the proportion of subscribers that either opt out or drop out of your list in a given period. Factors like the number of opt-outs, hard bounces, spam complaints, and subscriber inactivity are the main drivers behind list churn rates.

List churn tells you how fast your B2B contact leads database is shrinking. That’s why you need to acquire new contacts at a rate that exceeds the churn rate in order to grow your list. GetResponse estimates average annual list churn rates to be around 25%-30%.

 

  1. Spam Complaints/Reports

Every time a recipient marks your email as spam, you’re racking up spam complaints under your sender record. Once the number of spam complaints exceeds a given threshold, mailbox providers automatically classify your emails as junk. According to data from MailChimp, average spam complaint rates can vary from 0.01% to 0.04%, depending on the industry.

While spam complaints tend to reflect the quality of your email messages, they can also give you an idea about the quality of your B2B contact list. Email lists sometimes contain spam traps, which are email addresses created by mailbox providers to catch spammers red-handed. Clearly, it’s important that you find and remove this type of address from your B2B contacts leads database to help reduce the risk of incurring spam complaints.

Now, you know the crucial set of numbers that help you accurately gauge your contact list’s performance. To gain sharper insights on your B2B contact list, don’t just passively measure these metrics against industry benchmarks. Also actively run tests designed to optimize your database on a regular basis.

A 5-Point Data Hygiene Plan for Your B2B Contact Leads Database

A 5-Point Data Hygiene Plan for Your B2B Contact Leads Database

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You may not know it, but you’re wasting at least 12% of revenues due to bad marketing data. That’s according to a review from Econsultancy that says bad data tend to directly impact profitability in as much as 88% of companies.

That’s why proper data hygiene is as important as ever, since practically every marketer today makes decisions based on insights extracted from the data sitting in their CRM or prospect lists. In today’s post, we’ll go over the five key points you need to carefully consider in order to come up with an actionable data hygiene plan for your B2B contact leads database.

 

  1. Develop a thorough data maintenance routine.

Inaccurate data occupies just one segment    in the Venn diagram of bad data. There are other data quality issues—such as missing data, inconsistent data, duplicate data, and unsynchronized data—that you also have to watch out for.

So, you need data maintenance initiatives that both prevent and fix data quality issues at different stages of your data life cycle—from data collection all the way to data removal.

 

  1. Remove data barriers and silos.

In a typical B2B organization, it’s not uncommon to find multiple instances of the same piece of prospect data housed in separate locations (e.g., marketing automation platform for marketing and CRM database for sales). This increases the possibility of having unsynchronized, inconsistent, and misaligned information used by different teams.

A good data hygiene plan also needs to take into account potential barriers to the free flow of data across users, teams, and departments. There should only be one version of a piece of prospect information at any given time.

 

  1. Supplement manual with automated processes.

For best results, data hygiene should be carried out with the right mix of manual and automated data cleansing methods. While tools like AI and machine learning have now streamlined data hygiene tasks, there’s still a clear need to keep humans in the loop.

Take, for example, data deduplication. Most commercial data scrubbing packages come shipped with powerful deduplication capabilities, which are especially helpful for scrubbing a large B2B contact leads database. But the deduplication process still requires human input to correctly identify which redundant records to keep and which ones to discard.

 

  1. Rethink your entire data quality approach.

Another key point that your data hygiene action plan needs to address is to make data quality everyone’s concern. While you need to define clear roles and assign specific tasks for maintaining data quality, it’s equally important to make sure everybody’s onboard.

Also, keep in mind that you can’t manage what you can’t measure, so you need to choose a relevant set of KPIs and benchmarks to gauge how well your data hygiene initiatives are performing.

 

  1. Know when and how to look for expert help.

In some cases, outsourcing part of your data hygiene program to a data quality solutions provider is a more practical option than doing it yourself. For instance, enriching your prospect data for improved segmentation is best done with a third-party data provider, since doing this in-house can take up time and resources which could be better spent elsewhere.

So, take stock of your current data hygiene capabilities, and let a reputable data quality solutions provider handle those activities that you’d have a hard time carrying out in-house.

Now that you’ve nailed down what a data hygiene action plan should contain, it’s time for you to flesh out concrete ideas for maintaining data quality. Use these five points as guidelines, and be sure to track, test, and tweak your strategy.

Is Your B2B Contact Leads Database Ready for the AI Revolution?

Is Your B2B Contact/Leads Database Ready for the AI Revolution

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One of the main takeaways from Salesforce’s 2017 STATE of MARKETING report  is that investments in AI has outpaced spending in other marketing tech areas. B2B marketers are adopting AI technologies ranging from predictive lead scoring to chatbots in droves. But before you get caught up in the hype, there’s one thing you need to nail down before you start applying AI into your marketing processes: Is your B2B contact leads database ready for AI at all?

To answer this, we first need to separate the reality and the publicity behind AI’s capabilities in B2B marketing today. MarTech Advisor points to four key areas where B2B marketers can realistically expect AI to lend them a helping hand:

  • Scoring and ranking leads.
  • Segmentation and content personalization
  • Discovering and implementing Marketing automation strategies
  • Sales enablement and acceleration

At its present development stage, the best that AI technology can do is allow you to carry out the tasks in each of the above activities more efficiently. While some aspects of AI can uncover prospect behavior invisible to the unaided human B2B marketer, the reality is that AI remains just a tool, and tools are only as effective as the persons and processes using them.

So if you think AI has a place in your marketing toolkit, you first need to take a good look at your B2B contact leads database.

Like everything else in marketing, AI depends on good data. The data currently sitting in your CRM and datasets you’re about to collect need to meet some basic requirements before starting AI-enabled campaigns. In an interesting video series, Brandon Rohrer at Microsoft Azzure thinks of data science and AI as a lot like making pizza: the better the ingredients (your data), the better the final product (marketing insights).

There are four qualities that any dataset must satisfy to be ready for AI and data science:

  1. Relevant: Do the fields and records in your B2B contact leads database help you answer the questions you’re exploring? For example, which lead attributes in your CRM influence the likelihood that a prospect turns into a customer within the next quarter?
  2. Accurate: How reliable are the models/profiles generated from your marketing database? Do the records contain incorrect, outdated, redundant, or invalid entries?
  3. Connected: Are there significant gaps in your marketing data? What percentage of records contain empty fields?
  4. Sufficient: Do you have enough records to build robust AI models?

While each of the above criteria is important, we need to carefully consider sufficiency. AI requires data–lots of data. The algorithms that power most AI applications run on vast amounts of examples in their training set. In general, the more examples you use to train an AI algorithm, the more accurate the resulting model gets.

So before you think about applying AI in marketing, you first have to bring your contact leads database up to snuff.  Use the previous ideas as your guidelines and maximize the power of artificial intelligence.