Good customer experience has become a top focus for marketers in the past year, but if it’s going to be anything more than a buzz phrase, companies will need to put their data to work. Today’s customer expects a seamless, connected multichannel experience. In order for customers to do things like voice their problems on Facebook and receive a phone call in return, companies need to create a common thread through data. CMSwire details how to connect disparate data to create stellar customer experiences.
One example of this theory in practice is email marketing that reflects the messages prospects are receiving elsewhere. Business2Community describes how marketers who understand the sales cycle and the buyers’ journey created more effective emails. Many marketers still view email as a separate channel from all their other marketing activities, but this often results in messages that are off-putting to customers.
Part of the reason that marketing messages are disruptive rather than productive is lack of marketing and sales alignment. 1to1Media describes sales and marketing as two halves of an Oreo that require something to link to them together. The most effective “cement” for these two teams is a focus on customer success. When both teams prioritize the needs of the company brand over their own, they ultimately contribute to growth.
But it’s all talk, no action until someone actually knows how to manage big data. Understanding key goals and objectives is the first step. Along those lines, MarketingProfs outlines five big data principles to guide your marketing strategies. The article warns that “Big Data can be a Big Waste” if not done correctly.
FierceBigData points out another mistake marketers make: focusing more on the size of data sets rather than the tools themselves. Worry about whether or not you have “big data” is far less productive than putting in place the best-in-class to help you manage all your analytics. Focus on getting the right technology now, because your data sets will only get larger in the coming years.
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