There can only be a handful of companies in the world that do not claim to be focused on good customer service as a means to engender positive sentiments in clients and gain their loyalty and continued spend. In trying to deliver the best service, businesses have spent millions on customer relationship management (CRM) and related technologies, such as call centres and the agents needed to run them.
These call centre or customer service agents are frontline employees, those at the coalface of the modern corporation that have to deal with all manner of customer requests, complaints, suggestions and abuse. Even though these people are rarely responsible for business decisions and product flaws that affect clients, they are the first line of defence and often the only corporate face customers see.
Given the importance of the role these employees fulfil, one would expect them to receive a certain level of support from the company in terms of the tools and training. Unfortunately, no matter how well trained, equipped, motivated and remunerated employees are, if they can`t rely on the tools they`re provided with to do their jobs effectively, they may as well not be there.
In most cases of CRM and call centre ineffectiveness, it`s not the tools acting up, nor is it employees doing a poor job. Even the best, most expensive customer management tools are useless when populated with bad data. A call centre operator relies on the information on their screen to deliver an acceptable service to customers, and is powerless in the face of bad data.
Even the best, most expensive customer management tools are useless when populated with bad data.
Julian Field, MD, CenterField Software
When provided with incorrect information about a customer, they simply have to make excuses and muddle on as best as they can. In addition, their managers will still demand superhuman efforts, better results and shorter call times. Naturally, this has a destructive impact on staff as their motivation and, subsequently, productivity drops.
Moreover, once call centre agents accept that their data can not be trusted - generally after a few unpleasant customer interactions - they tend to adapt to the situation and resort to manual methods. In other words, the costly CRM application and equally costly data integration projects are wasted.
Once in this situation, the best a company can hope for is to spend more money on a data-cleansing project and hope it can convince employees - those left - to give the system another chance. However, the cost of cleansing bad data will be high and it is a time-consuming process:
* Hiring a person to correct a customer database would cost around R2 500 per day;
* Plus the cost of the calls that would need to be made to each client to confirm their details;
* Not to mention the non-financial cost of annoying customers with irritating phone calls.
* On average, one person would be able to call and correct data for 30 customers per day - an expensive course of action for companies with thousands of clients.
Looking beyond the impact bad data has on staff, including demoralisation and high turnover rates, the impact on revenue is exacerbated. In the first instance, annoyed customers are not likely to become repeat customers. Their comments and discussions with other customers and potential customers will, in all probability, negate any chance a company has of enticing them to trust it with their business.
Furthermore, lack of quality data will prevent staff from discovering cross- and up-selling opportunities and will also put a stop to the company discovering the current and lifetime value of each customer - a measure of how much effort it should put into each customer interaction.
Dirty data is far more than a technical issue that affects data warehousing and business intelligence projects. It reaches from databases housed in data centres, through the company to the front lines. At each step in the path, every employee, application and customer that interacts with the data is at risk because the information must be considered suspect. The best and most cost-effective defence against such risks is to ensure that corporate data is integrated and managed efficiently at the start of any customer-related projects, thereby ensuring its accuracy and quality.
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