Industrial companies: solve the first-party customer data equation with Data Quality!
Since the indirect sales model requires it, first-party customer data is a sought-after asset in the industry. Data quality helps to optimize data collection, customer repositories, and the relational campaigns of industrial companies.
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Today, industrial companies and manufacturers are facing the challenges of sectors opening up, and new entrants arriving. It has become strategically important to stand out, first and foremost, in an engaging customer relationship. Customer data is therefore an asset that must be used skillfully.
Now, in the industrial ecosystem, sales carried out via a network of resellers are very much the norm. Industrial players have little opportunity to be in direct contact with the end customer to collect first-party data. Data quality provides support to meet this challenge. From the customer experience to acquiring new qualified contacts, and including optimization of relational campaigns, data quality provides added value on multiple levels.
Input help enhances the customer experience in the industrial sector
In the industrial sector, direct data acquisition campaigns are strategic. In this field, industry players have to compensate for the lack of direct interaction with consumers and a low volume of customer information in their database. This is why they use targeted campaigns to collect new contacts.
In this context, providing an immediate positive experience is paramount, starting with the entry form, which is often the first interaction between a prospect and the company on the customer journey. Data quality makes this step easier thanks to input help: in real time, it signals an incorrect entry so that the user can immediately correct it. Autocompletion speeds up filling out various fields with suggested entries that are ready for the user to choose from.
Another benefit of data quality for prospects and customers of industrial companies is that, by applying the same quality rules to all collection sources, the resulting service after the implementation of the collected data is much smoother at all touchpoints. This is essential for providing an experience that is consistent and efficient.
Data quality reinforces the data management of industrial companies
Collecting customer data in an intermediated relationship requires allowing reliable and immediately usable data to be entered into the database. Input help is also a great asset in this respect. Real-time control ensures that users do not enter incorrect data. In addition, standardizing quality rules at all collection points makes data entry more reliable for all contact identification fields that are necessary for carrying out contracting.
Industrial companies enrich their customer repository with new reachable contacts, as well as data that is current and verified. Data quality thus makes it possible to get around the problem of customer data that can quickly change and that is poorly qualified. This facilitates data management, since business line users can rely on customer data without having to spend time and energy qualifying contacts after the fact.
Data quality is also a tool for enhancing indirect customer knowledge
In a competitive environment where each company must make itself stand out from others, industrial companies are cultivating a data-centric approach. Customer data, along with industrial data, are becoming assets that need to be skillfully deployed. However, customer relations primarily involve knowing and recognizing your customers in order to better target your offers and services.
In terms of customer knowledge, data quality makes it possible to eliminate duplicates in the customer repository. By deduplicating their databases, industrial companies avoid scenarios of confusion and approximation in the business line services that use the data. In addition, deduplication goes hand in hand with merging customer data according to the custom rules defined by the company. As a result, internal departments have complete, unique customer records that provide a 360-degree view of each contact, including their history with the company. Knowing and recognizing customers is imperative.
Qualified contacts boost relational campaigns
When data is qualified and deduplicated, it allows industrial companies to launch powerful relationship marketing programs.
On the one hand, contact data that is verified, reachable, and reliable significantly reduces a relational campaign’s bounce rate with each broadcast. The deliverability rate is optimal, which benefits the brand’s notoriety.
On the other hand, better customer knowledge based on quality data improves the impact of relational campaigns by addressing the right person with the right offer on the right channel.
This results in a much better ROI on the various campaigns, a very important aspect in highly targeted campaigns that have no margin for loss.
Data Quality makes life easier for internal services
Industrial data, customer and prospect data, and contact data from employees and numerous B2B customers: on all fronts, industrial companies must skillfully manage data. Only then can they give their business line users the means for carrying out their missions by making the most of their business line tools fed by quality data.
In this way data quality brings added value to various internal services. This is the case for HR, which, in industrial companies, often handles the data of thousands of employees. Input help and autocompletion of personal and contact data from employees, as well as the rectification of data in the HRIS database, allow them to optimize the performance of their business tools.
In terms of invoicing corporate customers, data quality also simplifies and makes the use of B2B data more reliable. Data quality makes it possible to enrich the collection of legal entity data by simply performing a call on the registration number or the company name on more than fifty fields generally present in company accounts. From the ERP, invoicing and addressing of invoices becomes more efficient, with data that is reliable, up to date and standardized. This skilled use of company legal data also makes it possible to easily comply with the obligations of dematerialized invoices.
About DQE
Because data quality is essential to customer knowledge and the construction of a lasting relationship, since 2008, DQE has provided its clients with innovative and comprehensive solutions that facilitate the collection of reliable data.
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