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Bertrand Duperrin's Library tagged customerinsight   View Popular, Search in Google

May
19
2012

"

Online, we often talk about listening to our customers on social channels to help make content decisions in marketing. Moving to a fully integrated marketing picture for enterprise, using social media to compliment traditional market and product development research only makes sense. The very nature of uncontrolled conversations empowers customers to communicate and yield unthought-of insights and new product directions.

However, most companies are still at the basic point of simply making Facebook and Twitter work, much less mastering content for marketing or social web-wide conversations. In fact, last autumn’s Global CMO Study from IBM confirmed that most enterprises just aren't there yet."

socialdata productdevelopment productdesign design listening data marketing customerinsight

    • While 82% of CMOs plan to increase social media use during the next three to five years, only 26% are currently tracking blogs, 42% are tracking third-party reviews, and 48% are tracking consumer reviews to help shape their marketing strategies.
    • 56% of CMOs view social media as a key engagement channel, but they still struggle with capturing valuable customer insight from the unstructured data that customers and potential customers produce.
  • The process can be broken into two main areas: 1) building listening stations and dashboards on relevant topics, and 2) sifting through the data to find actionable intelligence.
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Apr
10
2012

"Big data, unstructured data, semi-structured data. Data is all over the technology news, and for good reason. It is overwhelming most organizations; requiring new ways to operate to stay competitive; helping to serve customers better; and bringing new products to market faster. "

bigdata unstructureddatas customers customerservice customerinsight insights customercentricity data knowledge knowledgecapital

  • According to a recent IBM Survey of 1,500 CEOs, a staggering number of CEOs describe their organizations as data rich, but Insight poor and voice frustration at not being able to transform available data into feasible action plans, let alone detect emerging opportunities.
  • 9 more annotation(s)...
  • Unstructured data: Challenge or asset?
Jan
26
2012

"Nous entendons régulièrement des oracles prédire que désormais, grâce à la magie du 2.0, le monde de l'entreprise ne sera plus jamais comme avant.

Dans cette nouvelle ère, les structures hiérarchiques s'estompent. Les collaborateurs contribuent spontanément à l'innovation grâce aux réseaux sociaux inter-entreprises (les RSE) et grâce à une nouvelle dynamique coopérative. L'intelligence collective se structure spontanément pour traiter des situations de plus en plus complexes. Les ressources de l'entreprise sont spontanément utilisées à bon escient pour traiter des cas de plus en plus complexes et des situations de plus en plus individuelles, c'est l'ère du « Complex Event Management » et du « Case Management ». Dans ce monde, le client s'exprime naturellement et cette expression est représentative de la pensée de tous. Dans ce monde, le client contribue spontanément, directement ou au travers de l'analyse de ses réactions, à la définition des nouvelles offres de produits et de services."

enterprise2.0 socialbusiness process customerinsight socialnetworks

  • L’écoute de ses clients sur Facebook, sur les forums, sur son propre site requiert la mise en place de dispositifs industriels pour s’assurer que les billets sont analysés, triés, et font l’objet d’un suivi quand cela est nécessaire (cela s’appelle un processus).
  • Les RSE ne sont efficaces que si l’entreprise met en place un dispositif motivant les collaborateurs de l’entreprise à contribuer, à partager (par exemple, demander à chaque fin de mission à un collaborateur de publier les enseignements d’un projet, de partager les connaissances acquises), à réagir.
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"A team of IBM researchers spends their days sifting through Twitter. They use live streams of tweets to develop machines that are smarter than the typical computer, an area of study known as "machine learning."

Using these tweets, they've developed technology that allows a machine to understand that some tweets are just background noise and others are newsworthy and important."

ibm cognos customerinsight twitter sentiment sentimentanalysis

  • IBM scientists have also come up with ways to measure "sentiment" … to identify which tweets are saying something good about something important and which are saying something negative.
  • After two years of studying Twitter, their work wound up in an IBM social media monitoring product, Cognos Consumer Insight.
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