Accurate and up-to-date data is the lifeblood of any successful business. Maintaining clean CRM data is essential for effective operations, strategic decision-making, and superior customer experiences. Managing duplicates is one of the biggest challenges in keeping CRM data clean, especially when those duplicate records are created through integrations such as WhatsApp and Facebook Messenger. This often results in difficult-to-identify duplicates with partial data.
When data comes in through integrations, the integration may only have a small amount of data on the contact or account. For example, when a call is placed into your calling system, the system likely only knows the caller's phone number. If it cannot match that to an existing record, you will end up with a new contact with no name and just a phone number. Traditional deduplication methods, which rely on matching specific fields, struggle to identify duplicates accurately when a record only contains partial data. This leaves these integration-created records to languish and clutter your CRM database.
Enter the concept of deduplication by record creation date. This innovative approach allows you to filter records by their creation time, making it easier to spot duplicates that might otherwise go unnoticed. By focusing on when records were created, rather than relying solely on the data within them, you can significantly improve your deduplication process.
Insycle offers a powerful feature that helps businesses manage and merge duplicate records based on creation time. This simplifies the deduplication process and ensures your CRM data remains clean, accurate, and ready to drive business success.
Duplicate records can have far-reaching consequences for your business, affecting operations and efficiency. Duplicate records with very little data in them are destined never to be identified by standard CRM duplicate detection systems. They only have a chance of being merged if your company performs time-consuming manual merges.
Duplicate records complicate data management, leading to inefficiencies and wasted resources. For example, sales and marketing teams might spend unnecessary time sorting through multiple records to find accurate information. This detracts from their actual function, and is a widespread problem—in fact, sales reps are only actively selling 36% of the time due to duplicates and data roadblocks.
Let’s say a customer called your calling system from a number that did not exist in your system. Because the number was unrecognized, it was never connected back to an existing contact record. Now, important information from that call is housed on a record that will be difficult for a sales or support rep to find in your CRM, and that context will be effectively lost for good. This confusion can slow down processes, reduce productivity, and ultimately impact the bottom line.
Duplicate records and the lost context they cause can significantly harm customer relationships. When customers receive repeated communications or conflicting information, it can lead to frustration and erode trust in your brand. For instance, a customer might receive multiple marketing emails for the same campaign, or support teams might provide inconsistent information due to duplicate records. These issues damage the customer experience and tarnish your brand’s reputation.
Duplicates also pose operational challenges, particularly in reporting and analytics. Skewed data analytics resulting from duplicate records can lead to inaccurate reporting and poor decision-making. For example, call records housed on duplicate contacts might lead to undercounting a lead’s engagement, resulting in a lower lead score and less prioritization by your sales team.
Duplicate records can also demoralize employees by making their jobs harder to do effectively. When team members struggle to execute advanced strategies because they constantly battle data quality issues, their morale suffers. For instance, a sales team that has to cross-check multiple records for the same lead before making a call wastes valuable time and effort. This frustration can lead to decreased job satisfaction, lower commissions for reps, and increased turnover, costing the company both time and money.
Inaccurate data due to duplicates can severely impact top-down decision-making. When leadership relies on flawed data, it can lead to misguided strategies and poor business decisions. For instance, if duplicate records inflate contact counts, executives might overestimate market penetration and allocate resources inefficiently. This can result in missed opportunities, wasted budgets, and, ultimately, reduced competitiveness in the market.
Managing duplicate records is a significant challenge that impacts data management efficiency, customer relationships, employee morale, organizational culture, and top-down decision-making. The additional challenges of identifying and merging duplicate records containing only partial but important data—and with no way to do so in most CRM systems—eventually sends them scrambling for a solution.
Duplicate records in your CRM can create numerous pain points, complicating data management and affecting overall business efficiency. Understanding these challenges is crucial for implementing effective solutions and maintaining a high-quality database.
Traditional CRM deduplication methods typically match specific fields, such as email addresses, phone numbers, or names. However, when records are incomplete, these methods fall short. Incomplete data prevents accurate matching, leaving potential duplicates unrecognized and unresolved.
Additionally, leads coming in through Facebook Messenger are likely to only provide an individual's first and last name along with the chat logs. If an existing record in the system has the same first and last name, it would be difficult to determine whether it is the same person without manually diving into the chat context to figure it out.
Similarly, contacts created through WhatsApp integrations are likely only to provide a phone number—the WhatsApp number used during the chat. However, often, their existing contact record will have a traditional mobile number and not a WhatsApp phone number, meaning that you will never be able to identify the WhatsApp-created record as a duplicate record by phone number alone. Further, many CRM systems cannot normalize phone number data behind the scenes to identify duplicates, meaning that records listing the same phone number in multiple different formats may not be recognized as duplicates.
But there is a solution. Insycle allows you to identify potential duplicates by record creation date, making it easier for you to identify duplicates that may have come into your CRM system at the same time, but only with partial data.
Customers often engage with brands around the time they make a purchase. This is not a hard-and-fast rule, but it does happen often.
It is not uncommon for someone to engage with support through Facebook Messenger before going to the website and making a purchase. Similarly, they may need help or have questions immediately after making the purchase. This often leads to contacts being created twice in short succession—once when they buy the product, and once when they engage with support.
Insycle has a direct solution to deduplicating records created in scenarios just like these.
First, you need to set up the Merge Duplicates template to include the fields that you need to have matching to identify a duplicate. Often times, with integrations like WhatsApp and Facebook Messenger, you may only have a first name and last name to work with, if that.
Then, you can navigate to the Conditions tab in step one, and instruct Insycle to only identify duplicates that were created within a certain time frame of one another, with at least one record coming from Facebook Messenger, WhatsApp, or any similar integration. In the screenshot below, we are instructing Insycle to find duplicates where at least one of the duplicate records came in through WhatsApp, and all duplicate records were created within a two-hour timeframe. Please note that while often the integrated app name is stored on the "Original Source Drill-Down 2" field, sometimes it is on "Drill-Down 1", depending on the app.
It’s a powerful tool for ensuring that even those records with minimal data from integrated apps get flagged for review, enhancing the overall accuracy of your deduplication process.
Once you have a working template, you can automate it to run consistently on a set schedule to ensure that integration-created duplicates from channels like Facebook and WhatsApp are identified and merged to the best of your ability.
Insycle allows you to set criteria for automatic merging or to flag records for manual review. This flexibility ensures that you maintain control over the deduplication process in a way that works for your business while benefiting from increased accuracy and efficiency, decluttering your database as you go.
Managing duplicate records in a CRM is a complex challenge, especially when dealing with incomplete data from various entry points such as WhatsApp and Facebook Messenger. However, Insycle's innovative option for deduplication by record creation date offers a powerful solution. By filtering records based on their creation time, you can identify and merge duplicates that traditional methods might miss, ensuring your data remains accurate and reliable.
The benefits of this approach are clear: improved data quality, enhanced operational efficiency, better customer relationships, and more effective decision-making. Insycle's feature simplifies the deduplication process, allowing you to maintain a clean CRM database with minimal manual effort. This proactive strategy not only saves time and resources but also supports your business's overall growth and success.
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