This post is the first interview to four of the main experts in advanced analytics and customer insight (descriptive and predictive ones). The main aim of this interview is to get expert point of views about impacts and next developments on the social analytics field, especially when reconducted to the Social CRM topic.
Jim Sterne (from Wikipedia profile)
Jim Sterne is an author of business and marketing books, consultant, speaker, founder of the eMetrics Marketing Optimization Summit, and cofounder of the Web Analytics Association. In 1994, Sterne launched the first “Marketing on the Internet” seminar series. This eight-city tour was intended to promote the possibilities of using the Internet for advertising, marketing, sales, and customer service. In 2002, he founded an international conference series, the eMetrics Marketing Optimization Summit. Also since 2002, he publishes an email newsletter on web analytics called Sterne Measures. In 2003, Sterne cofounded the Web Analytics Association (WAA) together with consultants Bryan Eisenberg and Andrew Edwards. The WAA is composed of practitioners, consultants, and vendors dedicated to promoting a global understanding of web analytics. Sterne was named one of the 50 most influential people in digital marketing in 2006 by Revolution, the UK’s premier interactive marketing magazine.
One of the main problems that rise with the advent of Social CRM is the huge amount of unstructured data coming from the increasing number of social platforms and applications on the web. In your opinion, which is the better way to manage them for the successive insight and intelligence analyses? Will it be necessary to archive them all or do you think that filtering systems/specific access modality can (must) be applied? What do you think is necessary to pick up the more meaningful information in social data and how?
Archiving all that unstructured data can be useful provided it’s not simply too much. If people are publishing 50,000 videos per day, it’s just too much. The value of that sort of storage is the ability to ask historical questions. What was the mood of the marketplace in 2009 when our competitor launched their viral campaign. How has sentiment shifted over time? If that mood swing cyclical? Seasonal? I have always found that raw data is immensely valuable. Filtered and summarized data assumes that all of the questions are known in advance. The fact is, none of the best questions are known in advance, they are discovered during the analysis process.
During the last ITExpo Symposium 2010, Gartner has identified the 2011 Top 10 Strategic Technologies. Among these there are three that are directly connected to the Analytics world on which I’d like to hear your opinion. Let’s start with the most generic one: Social Analytics (Gartner says: “Social analytics is an umbrella term that includes a number of specialized analysis techniques such as social filtering, social-network analysis, sentiment analysis and social-media analytics”). Which do you think will be the possible developments of these techniques and their main support to the several aspects of Social CRM (advocate/influencer identification, proactive lead generation, etc.)?
There are four general metrics for social media: Reach (How many people got the message?), Attitude (How did the message change the sentiment of the marketplace?), Results (What actions did people take as a result of the message?) and Value (What was the impact on the organization in terms of revenue, savings or customer satisfaction?). Companies are interested in any tools that help in these areas and are going to invest in making them more efficient.
Now, what about Next Generation Analytics (Gartner says: “It is becoming possible to run simulations or models to predict the future outcome, rather than to simply provide backward looking data about past interactions, and to do these predictions in real-time to support each individual business action“)? Which will be the main Social CRM area that will benefit from the use of these predictive techniques, and how? Can you make some practical example?
Example 1, Customer Support – An individual – let’s call him Bill, files a complaint or just tweets about it. Reviewing Bill’s historical complaints, a system can predict the best approach to solving the problem and turning Bill into an advocate. Perhaps he should be corrected as his complaint is based on bad information. Maybe he responds better to apologies than offers of future discounts. In this case, the system itself may decide to tweet a link that solves the problem and thanks Bill for his interest or re-tweets the problem stating that it’s a common issue and then a link to an apology/explanation/special offer.
Example 2, Conversation Participation Alerts – Systems monitoring scope and sentiment can determine that the growing number of negative comments related to a specific product problem can notify corporate representatives to study the issue and make suggestions (as above) about the best ways and places to intervene and the most influential people to contact personally.
And finally what about Context-Aware Computing (Gartner says: “A contextually aware system anticipates the user’s needs and proactively serves up the most appropriate and customized content, product or service“)? How to really trigger coherent and proactive actions through social insight?
Given the ability to monitor and identify sentiment, systems are subjected to rules-based systems. Created by humans, these rules are modified over time by the system and its operators so that it is truly a “learning machine”. Today, websites can respond to multiple Back button clicks or mouse movements that indicate confusion or hesitancy and pop up an offer to speak to a customer service representative. Popping up alternative offers is a matter of human creativity and more sophisticate rules.
Do you believe that there are other important analytics techniques/technologies not considered in the Gartner forecast? If yes, which are and what are their business potentialities in Social CRM?
Social advertising and social search are very powerful and likely to become a more important part of the customer communication world. Tools that help organizations track, understand and derive insight from social activities are over the horizon at the moment, but will be imperative to the future success of companies.
In you opinion, there are vendors proposing interesting social descriptive and predictive analytical solutions? And how this market will develop in the next few months?
There are an enormous number of start-ups and giant analytics companies chasing after this marketplace. I have no doubt that the market will develop in fits and starts for a while and then really take off. The next phase will be consolidation. Just like any other bubble 😉
Thanks again to Jim and stay tuned for the other experts’ POVs.