Want to Have Your Customers at “Hello”? Personalize EVERYTHING
- The only way to personalize the customer experience is to base every interaction on real, specific customer data & preferences.
83% of consumers are willing to share personal information to enable personalization (Accenture).
68% of consumers believe it’s important for businesses to tailor experiences based on their tastes and preferences (Oracle).
33% of consumers ended their relationship with a company because the experience wasn’t personalized enough (Forbes).
No brand, regardless of vertical or industry, can ignore the overwhelming customer demand to personalize every engagement. You might say “what’s new? We have been talking about it for years”. Very true, yet it still is as big a problem as ever.
Why is that?
Because the only way to personalize the customer experience is to base every interaction on real, specific customer data and preferences. This also means responding in a matter of seconds (real-time).
The right message at the wrong time isn’t good enough anymore
For example, a customer who’s stuck or lost on your website or mobile app, isn’t going to wait around for a response that comes hours later. If anything, a late response often results in a negative reaction from customers, even if it’s personalized.
Personalization means interacting with customers at the right time, with the right contextual message, and on the right channel. As it turns out, it’s a huge challenge, both marketing and technology-wise.
With distributed data sources producing only fragmented customer journeys, customers are simply not getting what they want at the other end.
Organizations are often held back by their legacy stack, but more frustrating is the fact that even companies that are completely aware of the need and are fully prepared to tackle it head on, usually find themselves entangled in a painful data integration project.
Data integration doesn’t have to be painful
Up until now, data integration projects were long and expensive. Integrating data requires connecting all distributed data sources, moving all data to a single location, cleaning the data, and conveying it to the BI and marketing Automation Automation Automation is defined as the procedure of making an apparatus, a process, or a system to operate by mechanical or electronic devices that replace human labor. Additionally, automation is also sometimes referred to as mechanization or robotization. For example, employees have many costly needs, including government regulations. However, robotic workers don’t need much other than some routine maintenance and the occasional bug fix for an equipment malfunction or software bug. There is no overtime Automation is defined as the procedure of making an apparatus, a process, or a system to operate by mechanical or electronic devices that replace human labor. Additionally, automation is also sometimes referred to as mechanization or robotization. For example, employees have many costly needs, including government regulations. However, robotic workers don’t need much other than some routine maintenance and the occasional bug fix for an equipment malfunction or software bug. There is no overtime Read this Term tools, so that creative marketers can finally use it to engage with their customers.
Such projects also entail engaging with multiple vendors, and significant efforts and time need to be invested by the IT and R&D departments.
Even then, the outcome is often a limited number of business and marketing use cases. Even more challenging is the rigid data structure that doesn’t enable real-time communication, simply because of the way the data was handled – a “waterfall-like” process.
Moving data from its original source to final, trustable fact-tables, is the most complex, time-consuming part of the personalization process. Only then can the data be production-ready and usable. This process in of itself takes a long time.
In his piece “Looking ahead to the future of computing and data infrastructure”, Bucky Moore (Kleiner Perkins) says: “Now that all critical business data is centralized and readily accessible via SQL, the logical next step is to use this foundation to build full-featured applications that both read and write to the warehouse.... We will also see more start-ups attempting to reinvent existing categories like marketing automation, user event Analytics Analytics Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analyt Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analyt Read this Term, and customer support by building directly on top of the warehouse.” This is exactly what Solitics does.
Solitics’ technology changes the way companies communicate with their customers and enables easy integration with all data sources, in under 30 days, at a fraction of the cost.
Meet us at iFX Expo, May 19-20, Dubai, booth 83! To learn more, please visit solitics.com.
83% of consumers are willing to share personal information to enable personalization (Accenture).
68% of consumers believe it’s important for businesses to tailor experiences based on their tastes and preferences (Oracle).
33% of consumers ended their relationship with a company because the experience wasn’t personalized enough (Forbes).
No brand, regardless of vertical or industry, can ignore the overwhelming customer demand to personalize every engagement. You might say “what’s new? We have been talking about it for years”. Very true, yet it still is as big a problem as ever.
Why is that?
Because the only way to personalize the customer experience is to base every interaction on real, specific customer data and preferences. This also means responding in a matter of seconds (real-time).
The right message at the wrong time isn’t good enough anymore
For example, a customer who’s stuck or lost on your website or mobile app, isn’t going to wait around for a response that comes hours later. If anything, a late response often results in a negative reaction from customers, even if it’s personalized.
Personalization means interacting with customers at the right time, with the right contextual message, and on the right channel. As it turns out, it’s a huge challenge, both marketing and technology-wise.
With distributed data sources producing only fragmented customer journeys, customers are simply not getting what they want at the other end.
Organizations are often held back by their legacy stack, but more frustrating is the fact that even companies that are completely aware of the need and are fully prepared to tackle it head on, usually find themselves entangled in a painful data integration project.
Data integration doesn’t have to be painful
Up until now, data integration projects were long and expensive. Integrating data requires connecting all distributed data sources, moving all data to a single location, cleaning the data, and conveying it to the BI and marketing Automation Automation Automation is defined as the procedure of making an apparatus, a process, or a system to operate by mechanical or electronic devices that replace human labor. Additionally, automation is also sometimes referred to as mechanization or robotization. For example, employees have many costly needs, including government regulations. However, robotic workers don’t need much other than some routine maintenance and the occasional bug fix for an equipment malfunction or software bug. There is no overtime Automation is defined as the procedure of making an apparatus, a process, or a system to operate by mechanical or electronic devices that replace human labor. Additionally, automation is also sometimes referred to as mechanization or robotization. For example, employees have many costly needs, including government regulations. However, robotic workers don’t need much other than some routine maintenance and the occasional bug fix for an equipment malfunction or software bug. There is no overtime Read this Term tools, so that creative marketers can finally use it to engage with their customers.
Such projects also entail engaging with multiple vendors, and significant efforts and time need to be invested by the IT and R&D departments.
Even then, the outcome is often a limited number of business and marketing use cases. Even more challenging is the rigid data structure that doesn’t enable real-time communication, simply because of the way the data was handled – a “waterfall-like” process.
Moving data from its original source to final, trustable fact-tables, is the most complex, time-consuming part of the personalization process. Only then can the data be production-ready and usable. This process in of itself takes a long time.
In his piece “Looking ahead to the future of computing and data infrastructure”, Bucky Moore (Kleiner Perkins) says: “Now that all critical business data is centralized and readily accessible via SQL, the logical next step is to use this foundation to build full-featured applications that both read and write to the warehouse.... We will also see more start-ups attempting to reinvent existing categories like marketing automation, user event Analytics Analytics Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analyt Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analyt Read this Term, and customer support by building directly on top of the warehouse.” This is exactly what Solitics does.
Solitics’ technology changes the way companies communicate with their customers and enables easy integration with all data sources, in under 30 days, at a fraction of the cost.
Meet us at iFX Expo, May 19-20, Dubai, booth 83! To learn more, please visit solitics.com.