The benefits of CRM software are widely documented. When implemented properly, CRMs have been reported to improve client relationships, increase revenue and profitability, and improve the efficiency of sales teams.
However, the key phrase here is ‘when implemented properly’. Businesses that choose to use a new CRM will have challenges they must overcome to ensure high adoption rates.
These include the need for those at the organisation to get up to speed quickly with a new piece of software, and a way of working that may initially be unfamiliar.
Another factor, often overlooked in CRM implementation, is the way the software interacts with data. There are several challenges companies face when using data in a new CRM, including:
- Ensuring the data is rich enough to be useful.
- Keeping the data up to date.
- Formatting existing data into a new CRM.
- Organising data from several sources into the CRM, such as data from list brokers, a company’s existing data, and data gained from sales and marketing activities.
Failing to keep the data in a CRM clean can result in it being considerably less effective than it would otherwise be. Here are two examples of how a lack of clean data can affect CRM adoption.
Example One: Problems with Formatting Existing Data into a New CRM
Imagine an insurance company that has invested heavily in a new CRM. The CRM is perfect and does everything the company needs it to:
- It is cloud-based, so updates are reflected for all users as soon as they are made.
- It provides in-depth documentation and analysis capabilities.
- The dashboard looks great and is easy to use.
- The reporting tools help managers measure and drive activity.
- The CRM supplier provides a ton of resources and training for staff so they can get up to speed quickly.
However, when it comes to uploading the company’s existing data into the new CRM, things begin to get complicated:
- The data doesn’t match the CRM fields, meaning uploading and formatting the data is complex and tiresome.
- While everyone goes in with good intentions, staff aren’t updating the CRM data as much as they should – meaning the data quickly begins to decay.
- There are hundreds of thousands of records that are hard to differentiate; this means sales and marketing teams struggle to segment data effectively, resulting in an overall drop in their efficiency.
These factors mean the CRM isn’t working as it should, resulting in slower adoption. In the end, the otherwise decent CRM is brought down by a lack of clean, high-quality data.
Example Two: Static Prospect Lists Decay Quickly in Even the Best CRMs
Imagine a shopping centre looking to build a client base of suitable retailers. To help the sales team, management purchased a database of 50,000 UK retailers and uploaded the data into their CRM.
While the data all fits in the CRM, there are still some issues.
First, the data provided by the list is basic. It offers the sales team little more than the company location, contact details, and some basic financial metrics. This means it is difficult for sales teams to know where to start outreach.
Additionally, the data is static, meaning it doesn’t take long for it to become outdated. After a few months, the sales team notices that some retailers included in the list are no longer in business or are in considerable financial distress – time spent chasing these leads is wasted.
As the data becomes more and more outdated, managers consider purchasing another list. However, they worry this would result in the data from the two groups getting mixed up, and that the potential for duplicate entries is high. They also know they will be faced with the same problems a few months down the line.
What Makes Good CRM Data?
Good data has several characteristics that are missing from the data in the above examples.
- Relevance: Instead of buying a blanket list of potential customers and filling their CRM with unusable data, companies should target the businesses most likely to buy from them.
- Automatic Updates: The data should be connected to an outside source, so it is always up to date. This ensures sales teams always have access to the most relevant data from within the CRM and can free up reps from the responsibility of manually updating entries.
- Includes sales triggers: On UK businesses there are 100,000 data changes every single day – for example, when a company expands to a new area, when it gets a funding injection, or when a new director takes over the company. These changes should allow sales reps to target companies based on indicators that suggest they are likely to buy, but this can only happen if the data is updated in real time.
- Consistency: Data uploaded into the CRM should be configured to match the fields, so it is immediately useful and allows users to perform searches and find the information they need.
- Details: The more information a sales rep has on a prospect, the better he can qualify the lead and provide a sales presentation that addresses key customer pain points.
Red Flag Alert Data Is Perfect for CRMs
Businesses looking for a source of data to power their CRM should look no further than Red Flag Alert. Our API allows the data to be integrated into the most popular CRMs, including those from HubSpot, Pipedrive, Salesforce, Zoho, and Microsoft Dynamics.
Beyond this, the data has many features that make it perfect for use within a CRM:
- It includes data on 6.5 million UK businesses.
- It contains contact information on over 20 million key decision-makers.
- The data is updated over 100,000 times every day, eliminating data decay.
- The Red Flag Alert team will help you integrate the data into your CRM, cleaning out any old data in the process.
- We provide training to ensure everyone at your organisation can begin to take advantage of the data as soon as it is available.
To discuss how Red Flag Alert data can integrate with your CRM, get in touch with Richard West on 0344 412 6699, or at email@example.com.