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A few weeks ago, we announced the debut of a brand new feature - the Data Health Assessment.

This tool connects directly to CRM systems like HubSpot, Salesforce, and Intercom. Then, it analyzes your entire customer database and identifies more than 30+ of the most common customer data health issues.

In this article, we’ll dig into how your sales and marketing objectives are impacted by the data issues that are identified in the Health Assessment.

1. Accurate Data Helps Improve Marketing Segmentation, Personalization

In marketing operations, you have a few goals that are directly affected by the quality of your data.

First, you want to make sure that you are able to create effective customer profiles. The more data you can collect on your customers and prospects, the more effectively you can speak directly to their concerns.

Marketing automation is most effective when you are able to analyze engagement for specific customer personas. Different customer personas will engage differently with your content, product, and support teams. Accurate data helps you to better understand their concerns, preferred methods of engagement, and improve experiences for all customer segments.

A more well-rounded approach to data quality will also help you to identify new opportunities. Every company has gaps in their marketing and sales strategies. Effective customer segmentation allows you to hone in on the needs of specific customers and see what you are missing.

Most companies are sitting on a wealth of data that is going unused. There are many reasons why that data goes unused, but chief among those reasons is a lack of trust in the data itself.

Is the data clean? Is it accurate? Does it contain errors like typos or formatting considerations that may make it unusable or harm your brand reputation with customers?

It makes sense. Why would a company want to entrust their reputation to data when they don’t have processes in place to verify the quality? They shouldn’t, and most don’t. With the Data Health Assessment tool, you can identify and fix common data errors and give your team more confidence in how they use your data.

Among the common data errors that the Health Assessment will scan for include:

  • Records with missing data fields. It’s hard to ramp up marketing automation efforts if you have critical data missing from large portions of your customer records.
  • Standardize fields for consistency. You need consistent data to segment and organize leads. For instance, if you wanted to segment customer by state, there may be multiple ways a state name is recommended within your database (New York vs. NY vs. New York State, etc.)
  • Identify duplicates and deduplicate records using any data field. You don’t want to send the same marketing messaging to the same prospect twice.
  • Fix formatting issues. For instance, you can use Insycle to identify first names with capitalization issues. Would you rather your emails be addressed to “JANE,” “jane,” or “Jane?”

With confidence, you can do more.

2. Close More Sales with Improved Lead Scoring and Routing

In the past, we’ve written about how Insycle can help teams improve their lead scoring.

Effective lead scoring is critical for sales operations teams. With it, they are empowered to improve prospect prioritization. Companies want their sales teams to focus on the prospects that are most likely to result in new deals, and opportunities that present the highest revenue potential. Effective lead scoring makes for more productive salespeople.

Higher data quality means higher quality lead scoring. Your lead scoring initiatives rely on your data to appropriately analyze and prioritize leads. In the end, they raise their average customer lifetime value while losing fewer deals.

The thing is — all of that is only possible when you have reliable data feeding those lead scores.

Low quality data that contains errors, inaccuracies, and formatting issues leads to inaccurate lead scores, poor opportunity prioritization, and ultimately a less productive and satisfied sales team.

Using the Customer Data Health Assessment, you can identify and fix issues that keep leads from being scored or routed appropriately, including:

  • Contacts not associated with the right company. Contacts not associating with the right company can keep your leads from receiving an accurate score, causing your teams to prioritize the wrong leads.
  • Missing data fields causing inaccurate lead scores. When you are missing critical data, that data is not used in scoring your leads. For instance, a lead that works for a company that is missing its headcount can lead to great opportunities slipping through the cracks.
  • Inconsistent data leading to inaccurate lead scores. Inconsistent data can lead to problems scoring leads. For instance, maybe your company prioritized leads that are closer to your headquarters, assigning them higher lead scores based on their location. Using our “New York” example from earlier, platforms like HubSpot may not see “New York,” “NY,” and “New York State” as the same, and therefore inconsistent data would lead to wildly different lead scores.
  • Duplicate customer records cause confusion. Duplicate customer records can cause all sorts of confusion. It breaks the single customer view that helps you to deliver a consistent experience to each customer. It splits data between two profiles, so when your sales team is working from your CRM, they may be missing vital context that they need to speak more personally to that prospect.

These are just a few of the many ways in which the Health Assessment tool can help companies to improve their lead scoring and routing efforts.

Free Customer Data Health Assessment

3. Generate More Leads & Sales With Improved Conversion Optimization

More usable data means more data-backed decisions for marketing operations teams. In marketing operations, your have a few primary goals.

First and foremost — generate more quality leads. You want to keep your pipeline filled. To do so, you have to deliver messaging that consistently connects with a range of targeted customer personas.

There is nothing sales teams hate more than being delivered a batch of leads that aren’t ready to buy. With better marketing data, you will be more effective at nurturing prospects, identifying SQLs, and creating alignment between sales and marketing teams.

Once you have clean, reliable data, you can begin to inspect very specific elements of your marketing operations and sales operations processes. But without it? Good luck. You’ll just be taking shots in the dark

For instance, a roofing company might find that customers in different areas respond more positively to different pitches. A customer that is located in the mountains may be more concerned with how well a roof responds to heavy snowfall than a customer in a suburban community. With proper segmentation, you can make sure that you touch on those points whenever you engage with those customers.

Here’s how the Data Health Assessment can help companies to generate more leads, improve lead quality, and close more deals:

  • Identify duplicate customer and prospect records. Identify and merge duplicate customer records using any field (not just name and email). Maintain a single customer view throughout the customer lifecycle.
  • Improve personalization. When you have confidence that your data is correctly formatted and accurate, you can inject more personalization into your email campaigns and landing pages.
  • Gives sales teams more to work with. The more context your sales teams have on each prospect, the more effectively they can speak to the needs of each individual customer.

With clean data, you can run better split-tests and identify where improvements can be made, while planning for the future.

4. Plan for the Future with More Accurate Forecasting

Clean data makes for a better prepared, more organized company. It allows you to run more accurate forecasts, better share information between disconnected teams, and put your company in a position to make better data-backed decisions.

Many marketing and sales departments forego in-depth forecasts because of unreliable data. No one wants to make predictions or make large-scale decisions based on data that might be misleading.

Collecting data and failing to clean it is simply leaving money and critical information on the table.

For an accurate forecast, you need to do two high level things:

  • Create opportunities. Companies with poor quality data may have many potential opportunities floating out in the void — unidentified, and therefore, unactionable.
  • Track opportunities. For forecasting to work, sales reps need to enter data about the progress of their engagement, stages they reached, expected close date, opportunity amount etc. This requires accurate data that is correctly formatted.

In a simple forecast model you give each stage a probability and multiply that by the expected deal amount, and then use the expected close date.

For example, when you schedule a demo for your software product, the deal probability increases might increase to 20%. For a $10,000 deal with an expected close date of 12/31, a simple forecast calculation might look like this: 20% x $10,000 = $2,000 for 12/31.

But what if you have incomplete or stale data? For example, which opportunities do not have “close date” populated? Or that the “close date” is in the past? What about opportunities who have had the deal amount change as sales reps begin to learn more about the prospect?

More advanced models may factor in things like:

  • Number of contacts are associated to the company. How many people are involved in the process? The more contacts, the more likely it is moving in the right direction.
  • Last activity date. If there is no activity for the contact it decreases the probability of the sale closing.
  • Engagement from decision-makers. There may be many people involved in a deal, but ultimately it may come down to a final decision from a single, or a small group of decision-makers. Ultimately their level of engagement may play the biggest role in the likelihood of the deal closing.

For an accurate forecast you need reps to enter data. You also need a tool that surfaces the gaps in data or inconsistencies in that data. Then you can take them into account, point reps in the right direction, and improve time prioritization by focusing on the most impactful actions.

Speaking of impactful actions...

5. Reduce Churn in Subscription Businesses

Churn is the bane of any subscription business. Anticipating the needs of your customers plays a big role in reducing churn within SaaS companies. Churn rates hamper growth and lessen the impact of effective marketing and sales initiatives.

But to anticipate those needs, you need user data. You need to know what problems they are looking to solve with your solution.

With clean data, you can anticipate the needs of your customers and engage them in a way that feels personalized and genuine, increasing the chances that they remain a customer.

You need a way to track usage — or lack of usage — to determine where you need to step in. If a customer is inactive for a period of time, proactively reach out and figure out how to remedy any issues they’re having.

You can configure the Health Assessment to show you metrics that can help reduce churn. For example — users that haven’t signed up in the last week but haven’t gone through your initial onboarding steps.

Reducing churn is about smart prioritization. You can’t solve every problem for everyone. But you can focus on the best opportunities to save accounts.

6. Provide a Better Customer Experience

In a previous article, we covered how customer data plays a vital role throughout the customer lifecycle. Every step of the way, the quality of your data and breadth of its usage directly affects your ability to anticipate customer needs and speak directly, with context, about their experience with your brand.

Companies should strive to create a seamless and consistent experience throughout the customer lifecycle. Having a single customer view that all departments can use for context is critical for referencing previous engagements and leveraging what you already know about the customer.

To improve customer experiences, you have to identify where their experience problems lie. You can see where prospects fall out of the sales process, customers churn, and where friction keeps you from delivering a painless experience.

With the Data Health Assessment, you can:

  • Merge duplicates to enable a single customer view. One customer record means one place to look for engagement context for any department in your company.
  • Format and standardize data for reliable personalization. You can’t use data for personalization when you have no confidence in its accuracy.
  • Sync disconnected systems. Get rid of siloed data. Ensure that all stakeholders have access to the data that they need, when they need it.

Customers want to work with companies that can anticipate their needs and offer personalized solutions with a full context of the interactions that they have had with your brand over time.

To deliver that, you need alignment.

7. Create Alignment and Consistent Action with Simple Collaboration and Transparency

Do your marketing, sales, and customer support teams all have access to the same data? Can they work together to solve data-related issues that are holding both departments back?

In most companies, the answer is “no.”

Siloed data can be a serious problem that impedes alignment and reduces effectiveness across divisions and departments.

With the Data Health Assessment tool, there are a few key benefits that can help revenue operations teams to facilitate alignment:

  • Ongoing tracking and reporting. With the Health Assessment, you have a running tally of more than 30+ common customer data issues within your database. You can show management how, over time, you’ve improved data quality and improved marketing and sales effectiveness as a result.
  • Implement data strategy and SLAs. The Health Assessment dashboard promotes transparency. By creating custom templates, you can improve cross-team collaboration. Everyone will know what is expected of them and what data issues they need to watch out for. You can use custom templates to create a complete data quality workflow for your entire organization.
  • Built-in collaboration. No more passing messy Excel files back and forth through email and worrying about versions. Once you connect your HubSpot, Salesforce, or Intercom account to Insycle, anyone in your company with access to those platforms can sign up and begin cleaning your customer data through Insycle. You can save reports, views, and actions into templates, and share them using links.

Try the Insycle Data Health Assessment Today

All you have to do is login to your Insycle account, and you’ll have access to your updated Customer Data Health Assessment.

Once identified, our system makes navigation to the right tool and template to fix those issues within Insycle simple. All you have to do is click the “Fix” button and you’ll be directed to the right place - making identifying and fixing these issues a breeze.

In our announcement article, we covered the nuts and bolts of the Health Assessment. We looked at the different types of errors that the Health Assessment will help you identify while highlighting some of the different features offered through the tool.

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