"Managing" customer relationships till now involved recording "transactions" between company and the customer over phone, email and web-site besides "snail" mail and face-to-face exchanges and using the "historical" or "past" information to better serve the customers. Company was in total control of this conversation with customer at every stage. Information was recorded using pre-determined fields in the database, by company employees (or by contractors trained by the company) using script in CRM application controlled by the company. Thanks to the convergence of cloud computing, social media, predictive analytics and smart phones, this comfortable existence of marketers (and CIOs, CTOs as well) is about to come to an end.
Social Media has empowered customers like never before and they can discuss about brands/products on Social Media channels. This discussion is visible to all including other customers, potential customers and competitors.
Smart Phones/Portable devices with high speed internet access, geo-location tools and camera have ensured that customers can use information gained from Social Networks and Internet to maximum advantage. For example, scanning product bar codes to ascertain the lowest price of a product in geographical vicinity.
Software as a Service (SaaS) has made "on-demand" full functionality CRM application possible, with no large scale investments requirement upfront. CRM system's integration with multiple other systems was one of the biggest challenges, requiring substantial investment in terms of time and cost. No more, thanks to Cloud computing/SaaS model. It is possible to integrate SaaS and cloud applications with enterprise apps in days, what used to take weeks or even months earlier. This has further lowered entry barriers and made available complex, full featured CRM applications to small and medium sized firms - what so far was available to only companies with large IT/Marketing budgets, empowering smaller firms to compete with their larger rivals on equal footing.
And last but not least, predictive analytics has made it possible not only to analyse past customer behavior, but predict future behavior too based on statistical models. When combined with real-time Social Network data feed, it is THE killer app for next gen CRM system. Predictive analytics can help in identifying minor issues and help in taking corrective action before they become a crisis. For example, if a customer (or a group of customers) tweet about their dissatisfaction with a product or service, predictive analytics can help in identifying who among them are most likely to defect so that company can take corrective action before it is too late. Better still, if they happen to be customer(s) of a competitor, company can make an attractive offer and win them over. And thanks to SaaS model, this level of analytics functionality is available to small and medium sized companies with no large scale investments requirement upfront.
A good SMB CRM system can be an incredibly valuable asset for your business. As more businesses recognize this value, the amount of SMB CRM vendors is expanding quickly. Navigating the pricing plans, features, and service terms of all these can be a decision-making nightmare. more
One of the best ways to improve your customer service is to integrate your CRM and contact center software. Benefits of doing this include:Improved customer satisfaction through more personalized contacts, Better conversions on lead, and Increased employee productivity. more
Did you know that 67% of online consumers have used social media for customer service purposes?Unfortunately, many businesses ignore social mentions because they don’t know how to handle them appropriately. This is a problem because managing and responding to these mentions can make or break your brand. more
This whitepaper provides a guideline for selecting the right customer portal solution for your CRM by following a three-stage process. By comparing in-house and third party SaaS products, we examine present business and technical portal requirements, which are then mapped against the upfront and hidden costs for development and future scalability needs. more