Clean and organise your CRM database

The quality and structure of your Customer Relationship Management (CRM) database directly affects your organisation’s ability to segment audiences, personalise and automate communications and drive sales. 

Quality refers to the depth of information associated with contact or company records and the accuracy of that information, while the structure determines the ease of which that data can be accessed and used to deliver meaningful commercial actions.

Without a clean and consistent database, you will struggle to effectively implement relevant and meaningful sales and marketing strategies.  

CRM data standardisation:

At Kudos Media one of the most common issues we see when taking on new CRM clients is the use of free text data fields rather than standardised data fields.

Data standardisation is the process of ensuring consistency across the content and format of your CRM.

For example, “Job Title” as a free text data field might be any number of variations of the same position. By standardising this field into the positions your business most commonly deals with, you now have a defining characteristic that sales and marketing teams can leverage to segment by, report on and trigger automated communications to.

For instance, if you wanted to sell or market to a CEO you might create a case study or content specific to CEOs and then segment and target them with sales and marketing strategies. However, contacts could be listed as CEO, chief executive officers, C.E.O or perhaps even Managing Director making that segmentation difficult at best. 

Standardising your data fields overcomes this problem. 

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How to clean and consolidate your CRM data:

To clean and consolidate your CRM data, you should first understand the different points of data-entry and how the processes involved may lead to variations or duplication.

Are manually imported contacts collecting information in the same format as digital web-forms? Have your sales and customer service teams been trained to categorise (and enter!) customer information in the same way? It is important to determine and define how data will be formatted and stored.

To improve the quantity and quality of data over time, use re-engagement campaigns, lead generation campaigns including downloadable assets or other value exchanges and progressive profiling in digital web-forms. This process enables your database to self cleanse because existing customers or new prospects can self-select standardised fields when filling out forms or responding to requests for information.

It is also critical to train your sales representatives to manually select the key data fields that you want to know about your prospects, and to have an internal champion driving that adoption.

Knowing that data entry is not a strong point for most salespeople, Hubspot’s CRM has a number of automated data input tools to further minimise manual handling:

Email scanning: Automatically scans emails for records like names, job titles, phone numbers, and physical addresses, reducing the need for sales reps to enter them manually.

Business card scanner: HubSpot’s mobile app will automatically determine the first name, last name, email address, and more, and match them to your HubSpot properties

Deduplication: Merges duplicate contacts and companies and uses artificial intelligence to fix typos, nicknames, and abbreviation. It even works in large databases with millions of records.

CRM lead scoring:

Quality, standardised data provides sales teams with the context they need to have relevant conversations with qualified leads, and Huspot’s lead scoring makes it easy to differentiate between qualified and unqualified.

Lead scoring is the process of assigning value or ‘points’ to contacts or companies in your CRM – based on the data associated with them and their interactions with your marketing and communications – helping sales and marketing teams prioritise leads, deliver targeted content and conversations, and increase customer acquisition.

For example, you may assign more lead points to contacts listed as CEO and whose mobile number is known, than you do to contacts whose job title is unknown. 

This is only possible when data is standardised and strong data collection and management protocols are embraced, from the top of the business down.

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