Archive for the ‘Big Data’ Category

Analytics: Key part of Social Business Center of Excellence

Tuesday, February 14th, 2012

 So you want to build out a robust social media analytics program for your company, eh?

This process should be very similar to the approach you took in building out your digital analytics program. Follow the same trail to the summit.

Like any good journey, you need to make sure to focus on the basics first, such as:

    1. Getting internal alignment from you key stakeholders on your business objective (Hopefully, one objective!)
    2. Obtaining sign-off on the key metrics you want to look at
    3. Understanding your organizational constraints and resources
    4. Identifying and setting up the right tools/technology

But before launching a program, there are some important steps along the way that you should seriously consider:

    1. Work closely with your IT group because they usually set the standards for bringing technology into an enterprise environment
    2. Work closely and meet often with your financial partner (usually there is a finance guy assigned to your team) to show them that you are working on driving the business forward, that you understand what you are doing.
    3. Establish a baseline to measure from and know that every so often you might have to ‘move the goal line’ of desired results as well as the original baseline because your growth my skewed in the early stages of the program
    4. Incorporate Share of Voice vis a vis your direct competitors, your indirect competitors (if you are selling financial software to small businesses, excel can still be viewed as a competitor)
    5. Understand that there can be multiple ROIs for the whole organization since different groups have different objectives in using social media.
    6. Know that if you have an international focus, the same tools might not always work as the ones you use domestically
    7. Build in a mobile component to your social media analytics because as we all know, it is here to stay.

Most of the above applies to an enterprise type or Fortune 100 company. Ideally, the individuals working on measuring your success would be part of a Center of Excellence. Note, however, that this is more than the hub-spoke model, where your social media team resides in the middle with representatives from multiple groups.

One of the challenges with this model is that the groups representing the spokes are not funding a full time or part time person to look at social media, but rather having someone ‘just attend the meetings.’ Secondly, the Hub, the social media team tends to still be influenced by where they sit in the organization. If they sit with the public relations team or corporate communications team, those groups business objectives might not support others divisions. Ideally, I think Social Media today should be a true Center of Excellence, completely funded independently, and set up like finance or human resources, where the group assigns individuals to support others in the organizations.

This Center of Excellence idea is not completely new. The big difference here is that I am recommending it be treated like finance, legal or HR. Not in terms of being more of an operational role, but rather focused on a stand alone entity that embeds its own people into each group and pays for those people vs. having it be someone from a business group’s part time job. After talking to many companies about how they address social media in their organization, many wrestle with either a) individual groups doing their own thing or b) they only have a few hours a week of a business person’s time.

More on the center of excellence next time I blog here…

Oh yea.. Yes, your data jockey (s) should be part of this team too. : )

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Follow up to Webinar on Social Media Tools

Wednesday, January 18th, 2012

Here are the answers to the questions you sent us:

By — Scott Wilder, Gary Angel and Marshall Sponder

As usual I enjoyed the recent Social Media Measurement webinar – and it was great to have Marshall on as well. Tools always draw a crowd and this was no exception. Here’s the questions we got along with our joint answers…

Question: What tools are best for measuring social media ROI or business lift, with respect to advertising on Facebook, Twitter, Linkedin, etc

Marshall: There’s actually a new platform launching next week called Unified (UnifiedSocial.com – I will be at the launch) that promises to do something like that – I’ve seen the platform close up and I can tell you I am impressed.  It may be that 2012 will be a year where ROI will no longer be a totally elusive goal for social media.

Gary: This is far more difficult, I think, than people generally believe. The only easy path to ROI measurement is when user’s are either directly engaged in commerce on social sites (which is rare) or are directly clicking through to sites where they are engaged in commerce. In these cases, measurement is generally a straightforward application of existing Web analytics campaign tracking capabilities. Unfortunately, this isn’t often the case. In some cases, I’m not even sure that ROI is the proper path to measurement and where it is, I don’t think there is likely to be one answer or approach. If your Facebook advertising is directed toward increasing your Fanbase, you need to be able to measure the incremental value of Fan (and this won’t be one value by the way) to your marketing. Getting that measure takes a concerted research effort and won’t (in my opinion) be delivered by any single tool. I sometimes think that it might be better for organizations to – first glance – concentrate on the obvious optimizations points. It’s much easier to measure which campaigns generates engaged Fans and calculate their cost-efficiency in that respect. You can then optimize campaigns within the set of those targeted toward increasing your fanbase. It’s not ideal, but it is more practical.

Scott: In most cases, companies have to guestimate true ROI because of some of the limitations of the tools and also companies own infrastructure. I find it useful to create proxies – like determining cost estimates for certain activities, which in turn, would lead to a transaction.

 

Question: US cost is too high – example Engage121 is $1000 per month for first base level search – one profile with 3 seats.

Marshal: Well, as Gary pointed out, Engage121 is designed for a specific use case and type of client such as an airline or large franchised business with thousands of stores that each want a different response and editorial controls – think Dominos or Dunkin Donuts (though I think neither are Engage121 clients).  My point being, you can’t take the price of a platform in isolation from the use case and clients for whom it is designed and targeted to.  The Dominos and Dunkin’s of the world have plenty of money and need for this kind of platform – but if your looking for an “affordable point of entry” into Social Engagement- than go with HootSuite and be happy there are still some free platforms you can play with and get your feet wet.

Gary: Not every market is going to be served by a tool like Google Analytics – free and really good. I basically agree with Marshall here. One thing I will say that’s more general is that in my experience some pricing models are much worse than others for doing serious enterprise work. To do our kind of measurement (Semphonic) we need a pretty free hand to construct, test and use profiles of all sorts and we generally need quite a lot of them because all the interesting questions involve categorization. At the enterprise level, I’d much rather pay a significant lump sum for a pretty free hand with the data than have a pay-per-item model. Pay-per-item models tend to cripple analysis.

 

Question: Do you have preference for tools to measure public opinion about political candidates – public policy or litigation issues?

Marshall: Yes, I am working with one right now – 6Dgree.com – we are tracking two candidates in Rhode Island and breaking down their overlapping audiences – along with “persona” breakdowns of their twitter streams – here is what that looks like (I erased the names of the candidates because this is still in the very early exploratory stage of what works).

Politcal Social Image

So far, the persona development breakdown looks impressive, as we can break it down by various sub dimensions and the founders at 6Dgree are very willing to pursue my suggestions, which really impresses me about them.  So yes, as of now, I believe 6Dgree might have a winning platform at an affordable price level that works for Twitter and Facebook.  Another is PeekAnalytics, but it’s not adapted specifically to Politics, yet.

6Dgree has done some interesting work with Australian Labor party around issues and produces a weekly portal report that breaks down tweets around several issues – I’m impressed with the solution, but of course, each campaign is slightly different and customization will always be a fact of life.

 

Question: What are the better tools for global internal scale? If any? Or just by world region?

Marshall: I like Comscore Media Metrix for world reporting – but that’s mostly panel based reporting -but it does a fairly extensive job of categorization of lifestyle and interest across channels, countries and technologies such as video, mobile and search.

Gary: Ditto Marshall. I like NMIncite for many larger markets. Alterian provides excellent language coverage.

 

Question: Do you believe the sampling of data should include statistical testing? Or how do you ensure your sampling is reflective of the entire population to provide confidence in the recommendations?

Marshall Well, Gary has a pretty good post on that, written recently, and I think, rather than speak to it, I’ll let Gary address it http://semphonic.blogs.com/semangel/2011/11/the-limits-of-machine-analysis.html

Gary: Thanks for the plug! Let me know if the several blogs I’ve written on the subject don’t fully answer the question! Social Media Measurement is an odd blend of attempts to get universal coverage and hidden samples – which makes a single approach challenging. You can use statistical testing to measure the variations in your samples and, where possible (it isn’t at all levels) that’s certainly advisable.

 

Question: When one wants to search and analyze Twitter postings and the topic is very low salience, so likely a very, very small percentage of Twitter mentions in U.S. in a given week, what are the best ways to maximize the amount of Twitter Firehose that you search to catch as many Twitter postings on your low salience topic as possible?

Gary: Depending on your method of access, you might want to start by talking with your vendor (if you’re using a vendor to make the initial data pulls). The initial pull is often tunable. This also speaks to your ability to capture the topic in all its forms. Traditional keyword research of the type often done for long-tail SEO can be useful. There is a range of tools appropriate for this – we’ve also just used scanning tools to pull the text off of sites (both client Websites, communities, and competitors) to try and build rich topic profiles. You can also take advantage of wildcards (in some tools) to scan from hash tags that include but are not limited to your topic. Hash tag references are often concatenations of the topic with other words and are nearly always pertinent. Sometimes, too, you have to be creative about what you’re looking for. If, for instance, you’re launching a product that is distinct, you can’t expect to identify potential influencers by targeting the obvious words – they generally won’t have any traction. So you have to look for analogs that might allow you to find and target a reasonably set of influencers.

 

Q: Any views on Netbase, which SAP just partnered with?

Marshall: Yes, it seems like a good partnership. Netbase does a pretty good job at NLP and creating structure and meaning around unstructured social data, and rather than SAP trying to build that (or buy Netbase, which is an option) they just partnered with them.

Scott: Netbase is doing some really interesting stuff, especially when it comes to Netnography (see www. Netnography.com). I think the partnership with SAP will be good because I know that the company is putting a lot of energy into understanding their own segmentation better. We are doing some work for them right now. SAP is also making a big push in mobile analytics and would probably pull Netbase into.

 

Question: Gary, perhaps you could ask each speaker to summarize which tool they think is strongest in each of the three key use cases you’ve outlined?

Marshall: Here’s a list of companies to consider

  • For PR Effectiveness  - I’d say mPACT and Cision.
  • For Consumer Sentiment – I would recommend be NetBase (in fact) for its NLP capabilities.
  • For Social Campaign Effectiveness – Unified (once it launches)

Gary:

  • For PR Effectiveness: NMIncite – though it does a poor job with identifying influencers the segmentation is excellent for tracking them.
  • For Consumer Sentiment: Clarabridge and Crimson Hexagon – though we haven’t gotten to use Crimson Hexagon as much as we’d really like.
  • For Social Campaign Effectiveness: This is a tough one. Most of the new management tools provide some integrated reporting – but I think that really good effectiveness measurement demands that level of reporting plus Web analytics, plus traditional listening configured for the purpose, and maybe CRM-based extracts at the individual level as well (we sometimes analyze Facebook campaigns by extracting all the individuals and looking at their pre/post behavior).
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Big Data DNA !!

Tuesday, January 10th, 2012

Recently, a client told me that Big Data is an overused term. Unfortunately, it is also a relatively new area for marketers. A few years ago, bloggers started emphasizing the importance for CMOs to hire marketer who know technology, and now, there is a lot of commentary on the web about hiring data experts. In fact, one of the hot new job titles is data scientist.

One good thing about the Internet is that it has forced even traditional brand marketers to take a more rigorous approach towards analytics. Marketers have to get more data conscious focusing on customer data, prospect data, competitive data, online data, etc. They need to take a more holistic approach to data – and get Big Data thinking in their own DNA and into their team’s DNA.

BigData SW1 300x260 Big Data DNASlowly but surely this is happening. A recent eMarketer survey showed, however, there are still some inconsistencies in how it is defined. 48% of US Data practitioners defined big data as the ‘aggregate of external and internal web base data.’ 21% were unsure to how to even go about defining Big Data.

The  findings are a bit troubling, since Big Data is one of the top priorities of C-level leaders. For example, it is the number one concern of CIOs and is quickly becoming a big issue for marketers.

eMarketer highlighted the fact that more than half the companies they surveyed consider big data as a way to monitor competitors or their own brand. I would not call this Big Data analysis, however. Certainly using a Radian6 or a Scoutlabs  monitoring tool is not the same as doing Big Data analysis. Monitoring ‘what people are saying on the web’ rarely requires a lot of data crunching.

Besides coming up with a consistent definition of Big Data, we also need to find individuals to hire who now how to leverage the tools to crunch big data numbers, have the time to dedicate to a Big Data project, and have the experience to learn from their findings.

BigData SW2 273x300 Big Data DNAPutting definitions aside, it is clear that marketing departments need to get serious about Big Data (large data sets that can’t be handled by traditional tools) and focus on integrating the tools and resources for this area in their organization. I recommend that they hire someone who has experience in handling big data sets. Some of the idea characteristics include:

  • Intellectual curiosity and a strong desire to solve problems
  • Experience in data research
  • Open-mindedness and the ability to look at problems from different perspectives
  • A touch of skepticism to challenge traditional beliefs and practices
  • Ability to frame and communicate ideas based on data findings

After all, ‘if you can’t measure it, how are you going to improve on it?’

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THINK BIG data

Wednesday, January 4th, 2012

If you are looking to get ahead of your competition, think “Big Data.” It is one of the top issues that keeps the C-suite awake at night. And guess what. The data is just going to continue to grow and grow.

Recently, a McKinsey research study showed that it was one of the top priorities for CIOs and another study by Corporate Executive Board highlighted it as one of the key issues that CMOs face today.

Historically, these two groups rarely agreed on the biggest challenge(s) facing their organization. With the advent of social media and mobile mania, however, times are changing. Both CMOs and CIOs are now trying to figure out what just hit them; Few executives are prepared for this deluge of data. And few companies have the tools or the skilled workers to handle it.

Even though marketers are becoming more technical, they are still feeling challenged to decipher what the data is telling them. With all the talk of ROI, it is amazing how many CMOs still don’t understand the economics of their business. Unless they can figure this out, they will loose out to their competitors.

Managing this big elephant can be a strategic advantage for companies. Reid Hoffman, the founder of LinkedIn recently highlighted this in Fast Company.

As the activity in this space gets denser, it becomes important for [deals companies] to maintain their value proposition, both for the merchant and the consumer, and to be able to match the right two.

The ability to do that kind of matching, off the data, is the kind of thing that has a robust, at-scale, defensible value proposition and makes it harder for other people to offer products that are as good.

Reid, who is now also a venture capitalist recently said that each company in his portfolio will be asked to have a Big Data strategy. So, who will be drive this in a company? Marketers? IT folks? Marketers should get a head start and begin driving this — just like they often find themselves driving social media policies and training. I am not saying the social, mobile and big data are the same thing, but rather, Big Data offers another opportunity for marketers to play a leadership role in defining the vision and the requirements. And then partner with IT to ensure the right infrastructure in place.

Big Data is important because it enables marketers to slice the onion even thinner and develop more detailed customer segment information. In fact, some people are referring to this as ‘Digital Characteristics.’ Even more important, customer information can be refined and updated real time, leading to more customized promotions. Imagine tracking a mobile phone users behavior real time and adjusting your promotions accordingly. Or better yet, up-selling or cross-selling on their recent behavior.

So, I recommend following steps to take Big Data the basket:

  1. Make it part of your DNA; be clear (and communicate to the organization) why you are embracing big data – that it is not only a trendy phrase, but also a way of being;
  2. Create the mindset that this will be a journey where you will have to be flexible and not have your KPIs set in stone and that you will tweak them and refine them overtime (This is the way of being!)
  3. Hire a data scientist and a business analyst who have experience in handling large data sets
  4. Train each employee to think about data — (Note: But don’t only think about quantitative information because the qualitative data is just as important)
  5. Be open to a cross-functional approach (Hey marketers, you can lead this charge) to leveraging large amounts of information.
  6. Know that data will grow exponentially, so be prepared to build the infrastructure and to build an infrastructure that can (continue) to scale over time
  7. Meet several times a week to discuss the changing nature of your data and your business (meeting once a week is not enough)
  8. Understand that big data sets could kill the concept of sampling

And last, but not least, CMOs should think of CIOs as their ally when venturing on the Big Data journey. Together, they should work to understand and leverage the large data sets and extensive learnings coming from their customers behavior online. This information will provide insights that will lead to more innovation, better products and more sales.

How are you thinking about Big Data?

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