Cogensia is moving in the right direction by taking full advantage of the 2017 Loyalty Trends with our new CMP technology platform.
To meet consumer needs across the growing number of touch points: social, mobile, e-commerce, in-store and SMS brands must focus on generating a single customer view.
In 2017, brands will be challenged with developing true customer loyalty through personalization and relevancy.
It’s a mobile first world today. Consumers will look for functional apps that add value to their lives. Socially, brands will push past expected social media channels of Facebook, Twitter and LinkedIn to grow.
Technology is the great enabler for marketers. Data Services are King!
Big Data is transforming operations across the spectrum of industries and functions, including logistics, manufacturing, accounting, and even legal services. One key area often identified is marketing, specifically data-driven marketing. By tracking and analyzing customer interactions, the theory goes, a marketer can provide a higher level of relevance in marketing, including social media, email, real-time messaging, and mobile apps. While Big Data is described in many ways (unstructured, real-time, etc.), the key for marketers is to make sure there is a plan and tools to utilize Big Data to meet marketing objectives. For these purposes, Big Data will be described broadly, in terms of customer interactions regardless of channel. There are four factors that brands must assess to get the most of out their Big Data for CRM:
7 contrasts IT Executives need to know before making investments
Technology has upended industries, capabilities, and functions, and has the ability to automate a great number of tasks. The evolution of technology has meant the automation of more sophisticated tasks, including things like resume screening for HR, legal reviews of documents, and automated marketing communications.
Internal IT organizations are tasked with optimizing internal and external processes, vendors, and software to optimize the return on technology investment. This works well in operational and staff capabilities where processes are streamlined, and the inputs and outputs are well understood.
Marketing organizations, however, are a different breed. Marketers’ needs change; their ability to adapt to competitors, build loyalty, and test new campaigns and offers, across all digital and non-digital media. This causes their technology needs to be more complex. Methodologies, understanding of fickle customer interests and behaviors, and changing channels (Facebook rules, SEO changes) mean that the routine process of installing sophisticated software and tools and then moving on to the next initiative doesn’t apply.
About a week ago I was meeting with some of our analytic staff discussing differentiated strategies for distinct markets. It was one of those rare, fun conversations that extends beyond tactical needs of a project and really allows you to dig into strategy and (gasp) academic theory behind a methodology.
During the course of the conversation, the word ‘analytics’ was tossed around as it so often is. After what I considered to be enough patience, I finally interrupted the conversation to make a point. So many people use the term analytics for such a broad range of activities that it has functionally become meaningless. I have heard the term used as a description of the most basic reporting function; I have heard it used to describe the aspirational, strategic goals of some of the smartest marketers I have met. I wanted to point out to my young Padawans the impotence of throwing that word around, especially in the presence of an ‘analytic’ audience.
The response I received surprised me: I was asked, “So what does analytics mean (to you)?” I am sure many of you have been in a similar situation, where you have adopted a position (and probably it was well founded or researched) and had your talking points, but you haven’t really exhaustively thought about that position for quite some time. I didn’t have a rote answer or elevator speech to describe the essence of analytics. Sure, it is generically used to describe anything that touches data, and sure it is often used in a way that minimizes what it is that I do for a living, but when asked directly how I define it, I didn’t have a rehearsed response.