Questions? Call us now at +1-888-344-2652
In today’s competitive world gaining new customers and keeping them is a challenge. Many customers make rational decisions as to pricing, level of service they get and in the end any loyalty they have to their suppliers depends on different variables. Because of this customer behaviour, many businesses have begun to set up logical systems to track information regarding their customers’ communications, choices, likes and dislikes, price sensitivity and more.
CRM streamlines your business with automation to increase profits by creating a strategy for customer service. Depending on the different type of business, a customized CRM solution can make a big difference in the operations of the company. If your business is a call center, CRM system can provide a centralized database where your call center representatives have access to the customer information in one place. By doing this, your call center representatives will find important information quickly and the time spent to get access to important information will be reduced substantially. The result is that fewer employees are needed, and you will get more efficiency from those that you have. Knowing detailed information about your customers and prospects will help you gain more customers and keep existing ones. Your customers will feel important and understood with the personal information CRM provides.
Many companies are lacking a centralized database and integration of information within and amongst departments. For example a well customized CRM for your company can show information on the inventory, sales and marketing campaigns to appropriate people. Your sales representatives can view overstocked items and try to focus on selling these items more rather than waiting for a new item arrive. Your marketing representative can start a promotion of these over stock items.
A centralized database improves the efficiency of your business overall. Your business will benefit from implementing a CRM system which integrates all of your different departments in one place.
For more information about our services and products please contact us. Phone number: 1-888-344 2652 or 204-480 9772
Author: Aylin Barnes
Data quality is often addressed in the form of employees or vendor-supplied consultants, accounting for 20-50% of the data warehouse projects, labor over at least a few weeks and, in some cases, several months, depending on project size and complexity
Have you been underestimating data quality issue?
The most common perception is that low quality data is the result of existing and inadequate CRM, BI or integration applications. But surprisingly data quality is an issue that none of these applications can manage.
The performance of ERP, CRM, SCM or legacy systems in an enterprise demands that while data flows in and out of an operational data store, data warehouse or an integration data asset, its quality should remain untouched. The performance of other applications is dependent on the quality of data that it’s given to work on. So it is essential that data quality should act as a firewall for data coming from various sources. Only once the data gets clearance from the data quality norms, it should be sent to for data integration. From there it flows to the data warehouse where it can be accessed by different applications requesting it.
The main factors that render low quality to data are:
• Mismanaged data
• Inadequate data acquisition process
• Multiple data silos maintaining the same data
• Redundant data across multiple channels
• Ineffective data update process
It is important to identify the weak sources within an enterprise from where erroneous data flows. Over the years, enterprises tend to maintain data silos that keep expanding with faulty records. Due to disjointed network and insufficient integration capability, the data is further contaminated with erroneous information. Inaccurate, redundant and missing data continues to grow till it becomes an unmanageable set of fragmented and voluminous databases. Different systems are programmed to access data from the different faulty databases. CRM, ERP, BI and integration technologies that fail in enterprises are most often the result of substandard data.
Metadata is data about data. If the data comes with information about its source, author and other details, it is easier managed. And we have even seen metadata enabling optimal use of data. Hence, with all theinformation of source, time and context, metadata takes a lead role in defining the quality of data. Metadata is also known to be crucial for data warehousing. It acts as the link between the source and the data warehouse. It forms the semantic layer that becomes the basis of Business Intelligence applications.
So an enterprise has realized the importance of Data Quality. What now?
Once an enterprise realizes the importance of data quality within the enterprise, it is most important to acknowledge that it is not a one-time effort. Consistent data quality requires a process for improving the data quality metrics. Dedicated effort of a team of professionals is also crucial to the success of consistent high quality data. Both business and IT resources are invested to realize the benefits of data that is reliable, accurate and generated in short turn around time. The data quality methodology is a set of ongoing processes where data is organized, analyzed, qualified, used and updated. For each data repository, it is essential to set parameters for quality measurement. Identifying key metrics to quantify data helps measure the level of data usability in critical applications using it. The metrics should be able to reflect the ‘Return on Investment’ from the data being used.
More than 50 percent of business intelligence and customer relationship management deployments will suffer limited acceptance, if not outright failure, due to lack of attention to data quality issues.
The improvement process is a set of business cases and specific areas that need to be addressed. With the improvement areas, the goals and the priority attached with each should be clearly identified. Personnel responsible for executing each improvement task should clearly understand the entire execution process. The improvement process can be taken as the yardstick to measure future data quality improvement.
An enterprise’s ability to provide and maintain data quality depends on its people’s commitment towards consistent improvement. Business process and technology also contribute to high data quality. The mangers and quality personnel responsible for data quality need to identify and eliminate weak areas that lead to low quality of data. They should further ensure that data improvement plan is rigorously followed and improvement in data quality is measured. The metrics collected and collated become the input for the next cycle of data improvement. The process of maintaining and improving data has to be followed to establish a framework of data quality improvement. High data quality is a consistent effort for any enterprise.
Corporate Performance Management (CPM) is the new BI trend. It is the popular and matured capability of an enterprise with accelerated business drivers. CPM constitutes the set of guidelines that helps to manage the overall enterprise performance. It mandates a single view of critical and analytical information within the enterprise that helps decision makers to develop effective growth strategies. It helps to control the business processes as well as their responsiveness and effectiveness in the overall growth.
Even before starting a CPM initiative, it is important for engineers to determine the data quality, related metrics and business process to determine if the data will contribute to the success of CPM project. Success of similar concepts like Business Performance Management (BPM) and Enterprise Performance Management (EPM) also depend on the data that enters into such systems. Thus, data cleaning becomes an integral part for data residing in the data warehouse. There are several data quality tools that effectively analyze, map and qualify data to become input to CPM system. For every enterprise, before choosing a data quality tool, it is important to know the impact of the data on the CPM system.
Data warehouses and Business Intelligence applications like CPM are closely interconnected. The demand on these systems increases with the need to survive in a dynamic market. With a real time framework, an enterprise can consistently monitor and adapt quickly to changing requirements. Data quality and integration capability of enterprises is often challenged when there is a need to provide accurate, reliable and timely data to large number of service consumers with evolving demands. The complexity of the interconnected applications, warehouses and data sources can be simplified with the Service Oriented Architecture (SOA).
Based on open standards, the Service Oriented Architecture makes services available on a loosely coupled network. With SOA, data is available on an Enterprise Service Bus (ESB) that can be accessed by a large number of service consumers. With web services and XML at the core of SOA, it is easier and more flexible to readily adapt changes. In case of data quality tools, SOA enables its usage over the ESB as a service. This service can be accessed by a large number of users and applications over multiple business processes. As the data quality management process improves, SOA enables a greater flexibility to adapt to changes and generation of high quality data.
Questions? We can answer them. Contact us.
One of the keys to success is having a single view of your clients. Instead of having clients data, from sales contact history to service data, located in separate places, all the information on all your clients is pulled together into panoramic views of the customers.
Having a single perspective of your clients to all departments of your organization that service to the clients in different ways makes it easier to see the current communications and problems with that customer. Everything from the client's service history to sales records is pulled together in one place where all the employees who communicated with that client have access to the same records.
A single view of the client has many different advantages. One centralized data will keep all employees up to date and make them focus on the more latest and important issues with the clients. This practice increases client satisfaction, builds client loyalty and allows contacts with the customer to proceed much more smoothly.
A single, comprehensive customer record also presents a unified view of all aspects of the customer right at the contact's fingertips. Assuming the record is updated quickly, everyone from service to sales is on the same page with the customer.
Data synchronization across all departments is easy when a single record is used. If the client information is split between several databases managed by different departments it is much harder to keep everything consistent. A unified record prevents dissatisfaction with clients because different departments have one view of the customers.
This is also about expectations. The clients expect the companies to know the same things about them no matter which channel the client chooses for contact. This provides a unified experience and keeps the clients from having to answer the same questions over and over. From the companies' standpoint this doesn't sound like much, but repetition of basic information can be a major issue for the customer.
A single view of the customer not only helps manage customer contacts, it also makes it easier to produce precisely targeted sales efforts. This includes having the customer's sales history right at the sales force's fingertips when planning a campaign or looking for cross sale and up sales opportunities. It also makes it easier to anticipate the client’s needs, even before the customer recognizes them. This can result in more sales and larger sales to the same customer.
To be most effective, the single view of the customer must be supported by changes in the enterprise's organization. It is important that the various teams that have contact with the customer, such as sales, marketing, service, shipping, etc., communicate smoothly with each other. This usually involves direct communication between the teams rather than a hierarchical organization where communication travels up and down the hierarchy.
Clear communications among the teams makes it easier to keep everyone updated on the state of the customer in near-real-time. This is important because it helps keep everyone up to date on the customer and customer needs.
The technology of the organization usually needs to change as well. It must be fast enough to minimize the lag between the time something happens and the database is updated. For some organizations this means no change at all since they effectively update their customer records in real time. At the other end of the scale are organizations that only update once a day. This means the database is often out of synch with the reality and causes problems providing good service to customers.
Having a single, unified, view of the customer brings many advantages to the company. It may require some shifts in structure and perhaps spending money to upgrade your system, but the results are almost always worth it.
For more information please contact us.
ERP software has long been a tool for companies to centralize their data and improve data governance. Organizations are shifting their focus to big-data initiatives, and Enterprise Resource Planning is the number one sophisticated business intelligence for the operations of any company. Analytics is one of the standard features of ERP. ERP has built-in tools and easy-to-integrate add-ons that allow companies to make a quick shift towards real-time measurement, increased oversight and predictive analytics. The three main benefits of analytics for ERP include:
Faster decision making process
Improved product development
Reduced cost for organizations
Once companies apply business intelligence to high-quality data insights in an ERP that leads to opportunities to increase operational efficiency. For example, real-time dashboarding and data intelligence can facilitate improved decision-making among leadership, thereby increasing the organization's profits. Furthermore, shifting to a predictive model that includes social listening and other unstructured data analysis will allow businesses to discover new opportunities and quickly respond to customer demand. Interested? Learn more about the benefits of implementing an ERP with a robust BI tool, including dashboarding, reporting and data integrations.
Dashboards are simple data reports which provide clear oversight into operational performance by displaying a small set of key performance indicators (KPIs) that reveal company health.Using ERP BI tools to produce a daily or weekly data dashboard can allow organizations to:
Display the status of "mission-critical information"
Provide interactive features for improved decision-making
Allow users to sort by time period or other "drill down" functions
For many companies, simply moving towards a system of frequent, comprehensive oversight represents a significant improvement. However, the interactive nature of many ERP-driven data dashboards represents a new era of understanding for many business leaders. By being able to sort and interact with insights in real-time, leadership can gain a new and intimate understanding of how their decisions are impacting business outcomes.
Perhaps best of all, generating custom reporting in many ERP environments is not complex, and doesn't require the extensive custom code needed for reporting in many standalone BI applications. Analysts can benefit from a point-and-click, drag-and-drop environment to create custom insights at a moment's notice. The centralized nature of ERP eliminates the need for costly and time-consuming data integrations and quality checks, allowing data analysts to focus on simply telling the stories management needs to make decisions.
In many organizations, siloed data insights represents a key challenge. Organizations are often kept waiting for intelligence due to lengthy internal data sharing processes, or technology that's difficult or unreliable at integration.Five most common problems reported includes:
Difficulties in "drilling down"
ERP has the power to solve each of these problems. Analysts with the proper credentials are able to access insights from across the enterprise, from manufacturing to sales and accounting. This transparency can facilitate an immense amount of efficiency for reporting.Eliminating discrepancies and achieving the ability to "drill down" to answer specific questions requires deep integration, which is not only possible, but even simple, when your BI is backed by an enterprise-wide tool.
Implementation of a standalone BI resource can be costly and time consuming, and can also lead to mixed results. If your data assets aren't integrated and standardized across your enterprise, appreciating benefits quickly from an analytics initiative can be challenging due to the time required for integration, data standardization and the necessity to resolve quality errors.
For organizations with an existing ERP, using one of the robust BI plugins can allow for real-time decision-making and predictive capabilities. For other companies who have yet to implement ERP, it can represent a powerful way to quickly achieve total transparency.
For more information please contact us.
A successful sales process -- a systematic approach to track interaction with your prospects from their first point of contact through to the closing of a sale -- can generate bigger sales for your brand. Incomplete, inaccurate prospect and client data prevents your sales teams from nurturing prospects and connecting with clients. Customer Relations Management software can revolutionize your sales process by making it easier to negotiate with prospects and understand a buyer's process.
A large 2.5 quintillion bytes of data is produced every day, and 95 percent of the world's data is stored in a digital format. Your sales executive team need to go through reams of this data to monitor leads and qualify prospects. A Customer Relations Management system has a number of advantages over spreadsheet data entry: Reduced time for data entry, easy follow-ups with your customers and prospects, preventing data loss. Because CRM provides complete work flow automation, your sales teams spend less time typing, updating data and finding the information they need to close a sale.
With a Customer Relations Management system, data entry is no longer a time consuming process. Some systems let your sellers add customer details without having to enter a full address, or add social media pages for clients automatically.
With Customer Relations Management software your organization will have accurate data in place therefore it will result in shorter sales processes and accurate customer insights. Spreadsheet software is inaccurate and requires manual input, which could lead to data that is fraught with errors and inaccuracies. Programs like Excel make it difficult to review, understand and share data, something that could impact your sales process; however, when you incorporate a CRM system into your organization, your sales staff can access specific data about your targets, allowing them to move customers through the sales cycle.
Understanding and interpreting client data is crucial if you want to boost leads and communicate with prospects. More brands now realize the importance of client value -- 86 percent of marketers say their understanding of customers is increasing over time -- and having data in one place can facilitate accurate customer insights. According to CRM search, CRM should limit data entry to only the most necessary information, allow users to enter information using their keyboards and hot keys and be easy to navigate.
Lead generation is one of the most important components of any sales. This initial stage of the sales cycle -- before you qualify leads and convince prospects to sign up for your trial or purchase your product -- can be long and laborious.
CRM, however, lets you connect with high-value, good-quality leads and drive business growth. By using real-time data, your marketing teams can create personalized campaigns that enable customers to emotionally connect with your brand. For example, they can produce marketing material based on a target's likes, interests or purchasing habits.
Using CRM to improve your lead generation strategies can work wonders. Eighty-four percent of brands said CRM was "beneficial" when determining the quality of leads, while 45 percent of companies use CRM software to store lead data.
CRM shows no signs of slowing down. According to Gartner Research, the industry will be worth approximately $36 billion in 2017. If you want to simplify the sales process, CRM is a useful and powerful tool in your arsenal. This software automates data entry, provides you with accurate customer insights and generates better-quality leads.
Knowledge is the power in today’s competitive world. That is exactly how people should think of analytics. Data analytics is the process of discovery and algorithm work over large data sets to find trends, patterns, or similarities not easily seen by casual overview and reporting. This undertaking is half the process of using analytics. The second part of the process is making this knowledge available in a useable format.
In most organizations, marketing and sales are the first departments to get into analytics. These departments use the familiar database of the CRM system as the primary source of data for analytics projects. Customer Relations Management dealers increasingly build their systems with inputs from analytic processes and with places in the user interface or sales process to insert the output of advanced analytics.
This collection of data can take many forms, such as a recommended next product to pitch, purchase patterns and so on. With this functionality, marketing and sales teams are getting more accustomed to the system prompting them to take a recommended action.
Many sales teams have set up real-time analytics over their Customer Relations Management data. Real-time processes look at current activity, purchase history, and other buying patterns to provide actionable information right now.
For many organizations Enterprise Resource Planning system is their primary application after email and office productivity applications. The ERP system is where they perform tasks needed in business processes. Unfortunately, many ERP systems are old. Age is not a problem in and of itself; many older ERP systems operate just fine and have been getting business done for years. The problem for companies who roll out analytics beyond the marketing and sales departments is lack of user interface. Older Enterprise Resource Planning system’s standard screens and processes simply have no way to integrate and display data coming from advance analytics.
The way companies operate their business operations and their use of analytics is specific to each company’s employees’ and processes. In many organizations, analysis of Enterprise Resource Planning data usually happens well after the CRM data has been reviewed and experimented with several times over. As such, ERP users’ first understanding of analytics recommendations for action really comes from the CRM data. Common first data elements from CRM analytics often involve customer support and ongoing sales efforts. These data elements can include the previously mentioned product recommendations and sales timing as well as predicted events related to support or maintenance issues, depending on the industry.
The availability of data insights about upcoming events as a result of analytics is useless if that information is not in the hands of employees who can use the information for the benefits of the organization. Rather than create an additional application or rely on email to communicate needed actions, the ERP system needs to put recommended actions right into the flow of operations.
As many Enterprise Resource Planning systems do not natively offer a way to input data coming from analytical processes or a way to display those data in the user interface, there must be work done to customize the system to enable advanced analytics. Without this customization, the actionable information is going to be lost. Despite good intentions and internal communications about how to use analytical recommendations coming from the CRM data, businesspeople will keep on doing what they have always done. Thus, recommendations via only email or in a portal will go unused and even unlooked at.
Changing the ERP software to accommodate CRM-generated analytics is valuable, actionable information into the hands of businesspeople in a way that integrates with their current way of doing business.
For more information please contact us.
Maintaining your CRM database is an important job as you depend on the information everyday.That nice accurate database at the root of your CRM system will inevitably become corrupt and inaccurate over time. Incorrect entries are made, customers drop off, people change jobs or leave, and companies merge or go out of business. Slowly but surely your database becomes dirty, costing your people time and effort and your company lost opportunities.
However, just like most things, your CRM database needs to be cleaned regularly to remain useful and eliminate errors, duplication and outdated information. Ideally you do this as part of regular day to day operations. But even the most diligent organizations can often find this difficult. Less, ideally, your database can be scanned on a schedule and cleaned up at intervals.
But whether you do it on an ongoing or scheduled basis your lists of names, addresses, contacts, contact history and such need to be reviewed and corrected if your database is to remain at top efficiency. It may also be that, in your jurisdiction there are laws or regulations that define how long you can retain information, and how often it needs to be updated or refreshed.
The most straightforward way to do this is to have your people make corrections on the fly. Whenever they find an incorrect address, an obsolete listing or other error they correct it as they go.
This may sound simple but it isn't likely to be popular. This approach takes away from your salesforce's main job and interrupts their flow of work. It's better to schedule daily updates when your people can concentrate on cleaning up the data.
Daily updates are better than weekly or monthly updates because there is less chance for the incorrect data to be forgotten.
Pay special attention to people's names and company contact information. It's embarrassing to call a customer and ask for someone who left the company weeks ago. It doesn't get the sales call off to a good start. By the same token having a company name or address wrong makes an obvious bad impression as well.
You also need to eliminate duplicate entries, especially if your CRM system attaches the contact history with the client to the entry. If not corrected, this can lead to a system where you have two or more parallel and incompatible contact histories in your CRM database for the same company. This is confusing for everybody and does not make a good impression on the client.
This is a job that can be greatly aided by software. Some CRM packages come with a built-in deduplication feature which scans the database for similar or duplicate entries and flags them for possible combination. There are also third-party software packages available that can do the job. However, you don't want something that will automatically eliminate entries it sees as a duplicates as some of those “duplicates” may not actually be duplicates and the contact histories may need to be saved and/or merged.
The final stage in the process is to review the structure of your database at regular interviews and revise as needed. One common problem is asking the sales person to enter too much information in too many fields. It undoubtedly seemed like a good idea when the database was set up, but has it justified itself in practice? A lot of times it hasn't and it simply means extra work for the sales team.
It's important to make sure that the entries in the database serve the company as efficiency as possible. This means, among other things, storing the information that's needed and not cluttering up the entry with information of limited use.
However it's important to make sure that the information you want to eliminate isn't needed by someone. Be sure to check.
Data cleaning is one of those unglamorous and tedious jobs that needs to be done regularly to keep your CRM system running at top efficiency.
Are you a user of Sage CRM? If so, CRM Systems Group has tools available to clean, archive, purge and maintain your CRM system. Sometimes, automatically. We also have data quality tools that will help complete missing data, standardize data, and fill in gaps.
For more information about CRM and ERP please contact us.
CRM Systems is a full-service professional service provider of end-to-end ERP and CRM solutions for the SMB business market.
We are experts at what we do.
Contact us today for more information.
CRM Systems serves all of the United States and Canada with particular emphasis on the south-western USA, Ontario and western Canada.
Goudy Bookletter 1911