Nowadays, companies are using the Internet of Things (IoT) as a source of data. But, most companies are not using IoT data for their sales and marketing departments. We need to know the reason of this discrepancy. The gap is generally technical, and two different technical groups need to work together to tie the IoT to customer relationship management systems. This article explores the ways IoT data streams will improve the quality and impact of CRM data. They are : Usage rate, preventive maintenance and cross marketing. Read more at: http://it.toolbox.com/blogs/insidecrm/3-iot-data-streams-that-improve-the-quality-of-your-crm-data-74960

Constantly improvising on the quality of data is essential to remain ahead of business competition. However, failing to do so will result in a fatal erosion in the value of your most valuable asset, data, which is why it is vital to manage and maintain it effectively. 99% of marketers feel the urge to turn data into insights, yet 75% of organisations believe inaccurate data is undermining their ability to provide an excellent customer experience.

It’s impossible to provide outstanding customer experience with incomplete and incorrect customer data. However, improving the quality of your CRM data doesn’t have to be costly or time consuming.

Read here how you can effectively improve the quality of your CRM data: http://www.business2community.com/big-data/ensure-crm-data-fit-purpose-01706169#BufvU0yIxvoRxkdm.99

Advertisement program has been changed a lot from past years. Social media is the main advertisement platform. For social media, Salesforce is the foundation for managing customer relationships in the cloud, boasting a suite of solutions that helps users track customer journeys and deliver personalized, unique marketing experiences. Here are four ways to harness the power of Salesforce's CRM data to better personalize and customize customer experience: developing a journey map, build a beautifully-designed and user friendly website, use email to communicate with the customers, give product recommendations. Read more at: http://www.cmswire.com/customer-experience/4-ways-to-harness-salesforce-data-for-marketing-power/

Customer Relation Management is a combination of technology and collection of database of sales contact. This combination can be positively used to make a marketing strategy. This can be used to create awareness among the different departments of the organization, regarding the important actions that a customer has taken. Automated alerts can be sent notifying the important actions relevant to a team. Consistent messaging is required at times to stay in touch with the customer. This can be either with regard to feedback. Thus helping in getting insights of the customer. These practices help in understanding your customers in a better way. This improves your customer loyalty, hence resulting to improved engagement. Read more in the article written by Bruce Swann (Senior Product Marketing Manager for Adobe Campaign) at: http://blogs.adobe.com/digitalmarketing/digital-marketing/5-ways-crm-data-benefits-your-marketing-strategy/

Predictive analytics involve mining database for actionable insights on your customers and it aims to find patterns that will suggest sales strategies or tactics that will make your sales efforts more successful. It is a new tool for CRM. There are a number of third-party programs available that will enable you to apply predictive analytics to your CRM data, but, the cloud-based solutions are more attractive to small businesses. Read more at: http://it.toolbox.com/blogs/insidecrm/predictive-analytics-for-crm-70768

One area of analytics is machine learning. In earlier days, large companies could buy workstations and specialist software and employ highly educated people to look at their CRM data. The big change that makes machine learning with CRM data necessary today is the change in how customer interactions take place. Read more at: : http://it.toolbox.com/blogs/insidecrm/let-the-machines-do-the-marketing-machine-learning-with-crm-data-70746

Predictive analytics make better use of data. Nowadays, predictive analytics using CRM data deal with anticipating customer behavior. Mobile CRM is playing an important role to deploy predictive analytics. If mobile CRM and predictive analytics are merged, it is required that the right information is sent to the mobile app. It is predicted that in the future, mobile CRM might include the apps that customers use on their mobile devices and it is also predicted that smart devices and mobile CRM apps could listen to conversations that salespeople have with customers, which will in turn produce a pop-up message to the salesperson to recommend a product based on that discussion. Read more at: http://it.toolbox.com/blogs/insidecrm/mobile-crm-considerations-with-predictive-analytics-69606

The key to achieving better efficiency in CRM is through analytics. CRM will help sales teams to identify leads and retain customers. Marketing teams can use CRM to plan strategies for future. One should keep the following things in mind to successfully leverage CRM data:

(i) Data should be clean and devoid of bad data. Clean, filtered and structured data is essential for gaining meaningful insights.

(ii) Fixing systematic failures and finding ways to improve processes is important. Methods to capture data should not be broken. (iii) Adopting use of data quality tools so that one can use self-service tools and prepare data thus leading to improved productivity with progress of implementation.  

Read more at:http://www.business2community.com/big-data/taking-control-crm-data-01253472

In a manufacturing process everything is volatile and the main driver of that volatility is demand. Customer relationship management (CRM) system is the best place that reveals to us whether a product is in demand or not. The CRM system shows what will be bought and by whom. Earlier, assistants would gather data from people or reports, combine these data into spreadsheets, and then make the calculations. But, nowadays, dashboards are used to reduce the workload. David Gillman (Analyst with Studio B), writes in his article link about some common metrics that manufacturers need from the CRM system. Read more at: http://it.toolbox.com/blogs/insidecrm/crm-dashboard-data-that-matters-most-to-manufacturing-executives-66197

Data is important in any business and customer relationship management (CRM) systems collect volumes of data, plan for the future, learn from the past, and is also a target for hackers. The most important reason that hackers are target CRM data is that it allows them to conduct fraudulent transactions. Phishing is another reason. Hackers target CRM data for the purpose of social engineering, also called masquerading. Jerri Ledford (Analyst with Studio B), writes in her article about why hackers want CRM data. To know more, follow: http://it.toolbox.com/blogs/insidecrm/3-reasons-hackers-want-your-crm-data-66053

Nowadays, there are data breaches by which customer information is leaked. CRM data are highly confidential. There is no perfect system to protect all CRM data. But, some basic security measures can go a long way in creating a CRM security system. Read more at: http://it.toolbox.com/blogs/insidecrm/top-3-security-tips-for-your-crm-system-65549

Everyone, whether a salesperson or CEO, wants to increase sales and achieve higher margins. There are lots of sales methodology nowadays and these methodologies requires changes to the Customer Relationship Management (CRM). A new trend is also coming up- it is to use existing CRM data to predict prospect conversion. This process can be explained as: know who is a good prospect. To know more about how CRM data can predict prospect to customer conversion, follow David Gillman (expert in CRM systems)’s article link: : http://it.toolbox.com/blogs/insidecrm/using-crm-data-to-predict-prospecttocustomer-conversion-62893