Everybody, it seems, is getting onto the social media bandwagon. You can’t get far into any discussion about information management or marketing without it coming up, and it’s fascinating to see the emerging best practices and strategies behind social media products and consulting groups.
Here are five lessons from over a decade of working with Master Data Management, a much older piece of data-wrangling technology, that will serve any marketing or IT professional well as they navigate the social media technology landscape.
1. Huge Investments are a Tough Sell
I’m going to assume if you’re reading this that you see value in social media marketing, or else you see the potential for value. If you’re looking to leverage social media for your organization at a scale and level of sophistication higher than a summer intern firing off tweets now and then under the corporate handle, you’re going to have to actually spend money – and in an organization, that can be easier said than done.
Master Data Management teaches a very simple lesson on the subject of talking to your executives about a wonderful, intangible solution that will surely provide ROI if they can find it in themselves to approve the needed budget. The lesson is this: the bigger the price tag, the harder time you’ll have convincing a major decision maker it’s a necessary or worthwhile investment.
Often with MDM the more it’ll cost to implement, the more fantastic of an impact it will have on the data within the business. With social media, that’s a little harder to prove. It doesn’t help that there are more “social media marketing solutions” out there than you can shake a stick (or a corporate credit card) at.
If your executive doesn’t have time for your technobabble pitch for a million dollar overhaul, try wiggling your foot into the door by starting small without a lot of commitments. For MDM, that’s a proof-of-concept, and there’s no reason that can’t be applied to social media marketing. Consider starting off with something that is subscription based (my more IT-minded colleagues would refer to this as “software as a service” or “SaaS”) to give your management the confidence that if they aren’t seeing returns, they can just turn off the subscription and stop spending money on it.
This is your social media marketing proof-of-concept – if your initial test run gets you great results, that’s a good sign that your organization is part of an industry that stands to really benefit from a bigger, more expensive social media based project. Maybe even something that involves the term “big data”, but let’s not run before we walk.
2. Consolidated Records Mean More Accurate Information
This is the core premise of Master Data Management as an information management principle: you want there to be one copy of an important record that consolidates information from all its sources in the organization, containing only the most up to date and accurate data. It’s a simple but powerful idea, the philosophy of combining multiple copies of the same thing so that you only have one trustworthy copy, and then actively preventing new duplicates from cropping up.
The same thing applies to social media, especially when we’re talking about the users as actual human beings and not as individual accounts across multiple channels. Face it, we’re not interested in social media as an abstract concept – we’re there for the people using it.
(Which is why I love to cite this actual exchange between an older gentleman of a CEO and his marketing manager that goes something like: “I don’t get Twitter. I don’t use it, I don’t want to use it, I don’t personally know anybody that does use it, and I think it’s stupid.” “I agree. I honestly think it’s stupid too – but that doesn’t change the fact that 90% of our customer base uses it, and that’s why we need to pay attention to it.”)
So we’re there for the people – why on earth would we approach gathering and visualizing metrics and data on user accounts instead of people? Should we treat the Facebook, Pinterest, Twitter, LinkedIn and Tumblr account of one individual as having the weight of five individual voices?
What you really want to be looking for is a solution that matches and combines users across multiple channels. This isn’t quite the same process that it would be as part of MDM – this is new ground here that needs to be broken, and if you want to figure out that a Facebook user is the same person as a Twitter user, you need to be a little more creative than just checking to see if they have the same name.
With access to less traditional data (like a phone number or an address) it takes a bit of new technology combined with new approaches to match social media accounts accurately. I won’t bother getting into the details here, but suffice to say it’s something that today’s technology has the ability to do and a couple of companies are actually offering it. It seems perfectly logical to me that if you’re going to seriously use social media, especially in any sort of decision making process, you need to have a consolidated view of each user instead of a mishmash of unattributed accounts, which would, without a doubt, skew your numbers one way or another.
I’m going to briefly mention that if you want to take it a step above and beyond for even more insight into your customers, you can further consolidate that data by matching it to your internal records – Joe B in your client database is Joe B on Facebook and JoeTweet on Twitter, for example – but this is a much more ambitious project.
3. Data Quality is Not Just An IT Concern
Master Data Management is intended to bring greater value to an organization’s data by making it more accurate and trustworthy. Whether or not that actually happens very strongly depends on the quality of the data to begin with. As they say, “garbage in, garbage out,” and that’s even more true of social media marketing solutions. If you thought the quality of data in your organization was sorry to behold, I have a startling fact for you: the internet is full of garbage data. Absolutely overflowing with it. Not just things that are incorrect, but also things that are irrelevant.
If you’re going to get facts from social media, you’d better start taking data quality seriously – and make sure whatever solution you use is built by someone who takes it even more seriously. Let me give you an example.
Suppose you’re a retailer who sells Gucci products. You have a simple social media solution, a nice little application that gives you sentiment analysis and aggregate scores. You investigate how your different brands are doing and, to your shock, find that Gucci has a horrible sentiment rating. People are talking about the brand and boy are they unhappy.
You do some quick mental math and determine that it must be related to the promotion you just did around a new Gucci product. The customers must hate the product, or the promotion itself. You hurriedly show your CEO and she tells you to pull the ads.
What you didn’t know, and what your keyword based social media monitoring application didn’t know, is that there is a rap artist who goes by Gucci Mane whose fans tweet quite prolifically with reference to his name and an astonishing bouquet of language that the sentiment analysis algorithms determined to be highly negative.
Your customers are, in fact, pretty happy with Gucci and the most recent promotion, but the relevant data was drowned out and wildly skewed by a simple factor like a recording artist with a name in common. This wasn’t a question of “the data was wrong” – the data was accurate, it was just irrelevant, and the ability to distinguish between the two requires technology built on a foundation of data quality governance.
If you’re going to use social media data, especially when you’re using it as a measure for the success of a marketing campaign and subsequently the allocation of marketing budget, make sure you’re paying attention to data quality. Don’t veer away in alarm or boredom from terms like data governance just because they aren’t as sexy as SEO or content marketing or 360 view of the customer – train yourself to actively seek the references to data quality as part of the decision making process around a social media strategy.
4. Don’t Let Someone Else Define Your Business Rules
One of the most time consuming aspects of preparing for a Master Data Management implementation is sitting down to define your business rules. There is no one definition of the customer and no one definition of a product. These are complex issues that depend heavily on the unique needs and goals of an organization, and don’t let anybody try to tell you otherwise.
To that end, social media marketing demands the same level of complexity. If you’re building a social media strategy, you absolutely need to be thinking about those business rules and definitions. How do you define a suspect? A prospect? A customer? What makes someone important and worth targeting to you? Is it more important to you to have fifty potential leads or five leads that are defined by very specific requirements for qualification?
Every organization will be different, and a good social media solution takes that into account. Be wary of a piece of software or a consulting company that has a set of pre-established business rules that aren’t easily customizable or – even worse – are completely set in stone. If an outside company tries to tell you what your company’s priorities are and applies that same strategy to every single one of their clients, thank them for their time and look elsewhere.
Also steer clear of a solution that oversimplifies things. If you’re looking to social media opinion leaders as high value targets, you want to know how they’re defining that person as an opinion leader. Are they using one metric, like Klout score or number of followers? Are they using five? Would they be willing to give more emphasis to one over the other if your company places more value on, say, number of retweets than on number of likes?
Good solutions come preconfigured at a logical setting that is based on best practices and past client success – but are also flexible and able to match themselves to your unique business definitions and strategy as much as possible.
5. Data Silos Are Lost Opportunities
Finally, I want to talk about data silos. I’m going to expand on this term for those of you reading this who are marketing people like me and not necessarily information management junkies (although I confess the people who are both combined in one are always a delight to talk to). A data silo generally refers to situations in which the different lines of business hoard their databases and don’t like to share their information throughout the entire organization. This can be a huge problem for Master Data Management adoption, because of course the point is to make it so that everyone is using the same data, but it’s also a problem for social media marketing.
Social media data, first of all, is not just marketing data. Your sales teams will undoubtedly have uses for it in terms of account handling, and your product development teams, if you have them, will be interested in learning more about what customers actively crave from the market, and heck, your customer service division almost certainly can make use of an application that instantaneously warns them when people are dissatisfied.
The fact is, if you want to prove that gathering this data is useful, don’t hoard it all to yourself. Share that data around and let people play with it. Creativity – and creative ways to use data – happens when people think about things in ways they don’t normally think about them. Traditionally social media has been relegated to marketing, but it doesn’t have to be.
An ideal social media solution, even one of those affordable subscription-based ones I’ve been talking about, presents the data in an accessible, easily shared format. The good ones come with both a high level dashboard in business terms that even a CEO who thinks Twitter is stupid can log into and gain insight from and also the ability to drill down and export raw data so that the people who want to do complex and unique number crunching have that ability without the restraints of the program itself.
It’s important to have a good balance of goal-oriented strategy – never go into social media without a plan or a purpose – and openness to innovation. It’s even more important to be working with an application that accommodates both.
InfoTrellis is a premier consulting company in the MDM and Big Data space that is actively involved in the information management community and constantly striving to improve the value of CRM and Big Data to their customers. To learn more about Social Cue™, our social media SaaS offering, contact the InfoTrellis team directly at email@example.com to schedule a product demonstration.