The quality of their contact data in the customer relationship database is asked more often by decision-makers in companies than is suitable for an optimal sales result, especially when employees complain about their work and the actual effectiveness of such systems on a day-to-day basis. This article covers about the fews tips for the data quality
Sixty-six per cent of all inside sales managers would prefer to clean their bathroom instead of maintaining their CRM system. “This is the result of a study by the manufacturer Oracle.
In times of home offices, in which the bathroom is not too far away, this is clear As a manager, refusing to work with a CRM system should be avoided because: If the CRM system is misused, users can quickly lose their pleasure and reach their limits, and productivity is more damaged than at first Look thought.
Most of the problems arise from a missing or incomplete integration of the CRM within the own Information Technology landscape. Many employees, not just those in sales, use up to eight different applications for their daily work.
The relevant data for the user should ideally all be available in good quality integrated with the CRM and not be indifferent systems. Most errors occur during repetitive, time-consuming administrative tasks.
Nobody wants to maintain conversation notes twice in two different applications. Likewise, nobody wants to worry about manually synchronizing customer data.
It is, therefore, crucial to ensure complete integration right from the start when introducing CRM. Since this is unfortunately often not the case in practice, the following tip will help at the beginning: It is better to connect fewer systems, but all of them.
In customer relationship management, data avoidance and data economy are often forgotten. Often customer data is stored that is not necessary for the fulfilment of an order or contract. This can be due to the requirements of the superior, but also to the lack of sensitivity on the part of the employee.
So prioritize the number of “important dates”. Better just five to ten attributes per company and contact person, but they are well maintained. This also means having a high degree of filling.
Data economy helps to reduce the feeling that data maintenance is a time-waster. An additional effect: the strategic data economy minimizes the additional risk of a possible violation of the GDPR.
One step towards simplification is the use of modern care solutions. Many sales employees still like to work with pen and paper, because in practice, a meeting is often only recorded with an informal note.
If there are no notes in the meantime, they will be made quickly and without structure after an appointment. Often there is a lack of form or design so that colleagues cannot understand the result of the conversation.
Avoiding a handwritten or incomprehensible note, for example, can largely be avoided with voice recording. With voice input, the employee captures the information directly after a meeting. This function enables data to be recorded at any time, including in the car.
A speech-to-text interface then stores a usable note in the system for everyone. In this way, the follow-up of a conversation takes place without loss of time and information.
The subject of a short-term premium is often critically examined in practice. The following mindset often prevails among managers: “I am already paying for this task. For this reason, no additional bonus can be justified.”
With this attitude, the manager has given himself this critical task of ensuring the best possible data quality. It must use management methods to ensure that data maintenance takes place as desired and that it is reflected in the behaviour of employees in the long term.
The managers must provide the necessary intrinsic motivation (from within) through achievable objectives and their guidance. Experience shows: this is very time-consuming, demanding and therefore often without great success.
As with Pavlov’s dog, bonuses lead to extrinsic motivation. If the awarding of prizes is maintained for a more extended period, the work steps for maintenance are incorporated into daily routine behaviour.
This tip takes up the assessments already made in tip 4. The proper methods in strategic employee management are a big step towards high quality. As a manager, it is essential to ensure that a CRM system is fully incorporated into its culture and processes.
The introduction of a new system often entails additional work due to changes in behaviour and thus resistance. The best way for a manager to counter this resistance is to reduce tasks in advance.
Anyone who demands even more from their employees who are already busy before the introduction can only compensate for this by relieving them. In addition to reducing the burden, it also includes ordering regular training courses for new modules. Only those who train regularly can make the process effective.
For this, it is important to define goals. A goal can be, for example, the rate of wholly recorded contacts. If this goal is met, the employee is valued in the form of bonuses. These long-term bonuses can be scaled back over time.
The reason: the behaviour has passed into a routine that is now reinforced by the results of a well-maintained CRM system.
How can a term that you know from a call centre apply to mine CRM help when it comes to data quality? At first glance, this counter-question is entirely justified.
The Average Handling Time (AHT) takes up the criterion of correct guidance described under tip five again. Determining an AHT can have a significant influence on the maintenance of the data in CRM systems.
A processing time can be defined for maintaining customer contact. A lump sum that should be spent on follow-up, maintenance, or data enrichment does not make sense. A target for the average processing time based on customer value and customer behaviour is more effective.
For customers with a solid contribution to achieving a company goal, a higher maintenance effort is justified, which may exceed the usual level. The same rules apply to prospects and customers with high customer value potential.
The same applies here: less is more. When employees are instructed to recognize a customer’s potential, they already allocate the necessary time budget. In the further course, poor data quality does not become a problem.
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