At the beginning of the year it looked like 2014 was shaping up to be a year when Small Data moved out of the shadows and into the mainstream (or maybe even THE Year of Small Data as I predicted in this op-ed for ZDNet). Judging by the volume of articles, social chatter, and casual conversation I’ve had at numerous industry events, Small Data has arrived. But it still means different things to different people. And that’s cool, since there’s a lot we’ve learned over the past couple years about why it’s important – not only as an alternative to Big Data – but also as a design philosophy and movement that shifts the conversation from processing power…to people!
So if you’re new to the topic, or just curious how Small Data has grown up, I’ve collected my “Top 10” articles for sampling the early concepts as well as the latest thinking. There are many more pieces I’ve left off, but this might serve as a core reading list. And yes, I’ve included just 2 of my own articles, but if you like them you can find many more on this blog or on the Actuate buzz page.
The Early Days – Foundations
Forget Big Data, Small Data is the Real Revolution – Rufus Pollock’s (@rufuspollock) original post on the power of Small Data, collaboration and “decentralized data wrangling” from April 2013. Consistently one of the top 5 most cited pieces on the topic, it’s a great companion to my Forbes piece below.
These Smart, Social Apps Bring Big Data Down to Size – my piece with Mark Fidelman (@markfidelman) from October 2012 that introduced the pillars of small data design: make it simple, be smart, think mobile (be responsive) and predicted a new wave of user-centric business intelligence.
What happens when each patient becomes their own “universe” of unique medical data? – Prof. Deborah Estrin (of @cornell_tech) talk at TEDMed 2013 has key ideas around managing our own personal Small Data. Especially relevant to not only privacy discussions but also those pondering the next wave of wearables and fitness tracking devices.
Data-driven Marketing – 3 Perspectives
Small Data Can Help Businesses Be More Human – great post on the need for “human scale” in marketing by Brand Networks CEO Jamie Tedford (@jamietedford).
What the “Small Data” Revolution Means for Marketers – it’s all about delivering more targeted, more personalized and all-around more intelligent marketing campaigns says CommandIQ (@CommandIQ) CEO Noah Jessop. Right on!
What’s The Big Deal About ‘Small Data’? – recent roundup of perspectives on the marketing front (yup, including my own) by my friends at CMO.com.
Is Small the New Big? – Mainstream Thinking and New Voices
Focus on data value, not its ‘bigness’ – one of my recent op-eds on data value, decentralization and the new CRM. Good overview piece if you want to get a high level perspective and stir up thinking within your own organization.
In Praise of ‘Small Data’: How Targeted Analytics — Not ‘Big Data’ — Are Transforming Education Today – new post by Brian Kibby (@BrianKibby), President of McGraw-Hill’s Higher Education Group.
Your Sushi May Be Getting Smarter – new piece in The Atlantic by Tech Editor Adrienne LaFrance (@AdrienneLaF) on “smart objects,” food safety and the power of Small Data (and IoT).
How To Create Incredible Customer Service Through The ‘Small Data’ Advantage – new piece by customer service speaker and author Micah Solomon (@micahsolomon). While a lot of my focus to-date has been on marketing use cases, I think there are some great ones in customer service/loyalty as well as this post suggests.
What articles did I miss? What would you add if I made it a “top 20” list instead?
Big data has never been bigger. On the heals of a new study (reported here) that shows that investors have pumped $3.6 billion into big data startups this year, and Gartner’s latest Hype Cycle which shows big data quickly approaching the top of the hype “cliff” (along with Consumer 3D Printing and Gamification), one is tempted to see more of the same in 2014. Yet all the steam coming out of the big data hype machine seems to be obscuring our view of the big picture: in many cases big data is overkill. And in most cases big data is useful only if we can do something with it in our everyday jobs.
Which is why against the backdrop of more hype (and more confusion) about the real role for big data, the case for thinking small looks more and more attractive. In fact, I recently penned an opinion piece for ZDNet in Paul Greenberg’s excellent column on Social CRM on 10 Reasons 2014 will be the Year of Small Data. You can read the full piece here, and here’s the Cliffs Notes version of the first 5 reasons:
- Big data is hard. Doing it at scale takes time, especially when the tech guys own it (I used to be a data scientist, so I can say this!).
- Small data is all around us. Social and mobile signals can help us understand customer needs – today.
- Small data powers the new CRM. Small data is central to the rich profiles essential to targeting offers and experiences.
- ROI is the thing. To realize the full value of data-driven apps they must be accessible, understandable, and actionable for everyday work (remember our definition).
- Data-driven marketing is the next wave. As more consumers want to access, and consume and even wear useful data, there’s an unprecedented opportunity for savvy marketers and platform providers like Adobe, HubSpot, and Salesforce, along with data specialists and tool providers like Actuate, Localytics, TrueLens, and Visible to power the next wave of apps, experiences and devices.
What do you think? Are you finalizing your big and small data strategy for 2014? If you’d like DCG’s perspectives as you formulate your plans I’ll be hosting a special Webinar on Dec 12 at 1:00pm ET to share our outlook and 2014 research agenda. Hope to see you there!
UPDATE: missed my Webinar? You can view the replay by clicking here.
Reaching and engaging today’s social, mobile consumer creates unique challenges for retailers. With more than one billion Facebook users, and nearly everyone on the planet with a mobile phone, there’s never been more potential to reach new audiences, deliver compelling omni-channel experiences, and gather new insights on consumer likes and dislikes. Yet these same trends have also created new distractions, potential threats (and opportunities) from the phenomenon of “showrooming,” and a shortage of expertise for sifting through and make sense of a growing mountain of customer data.
Against this backdrop, the importance of connecting with buyers via tailored offers, recommendations, and experiences has never been more important. Even in B2B, among best-in-class content marketers, 71% tailor content to a profile of the decision maker, according to a recent CMI/MarketingProfs study. But at the same time, delivering convenience and bringing your brand and data to where your customers are, and factoring in the role of influencers, product reviews, and word of mouth needs to be in the mix as well. Clearly, in this environment, merchandising is both an art and a science!
This is why I’ve been seeing a tremendous opportunity for retailers who embrace their customer data as a both an asset and a product, and also invest in the notion of small data by tapping digital breadcrumbs, social signals, and profile information (as sources) and committing to making insights actionable and available to (the broadest set of) staff and customers alike. In fact it’s a theme that I’ve validated in several discussions with retail consultants, planners, and merchandising professionals over the past several months.
The end goal is greater understanding, better performing campaigns, and a more rewarding experience for your customers.
More specifically, as I recently discussed in a Digital Clarity Group Brief sponsored by my friends at SDL (you can download the paper as well as some excellent presentations here), it’s clear that:
- Retailers can boost their understanding of customers and better serve them (on their own terms) across all channels by looking to blend transactional processes and insights with social interactions and data.
- Innovators are focusing on making insights actionable via recommendations and predictive targeting, smart apps/kiosks for associates, and location-based offers.
- There are clear benefits to thinking small – targeting local campaigns and data, starting with high potential segments, and streamlining key stages of the path to purchase.
Most importantly, we can’t forget to ask customers what they think. Encourage social feedback and make it easy to share offers with friends. If you can’t measure it (conversions, sharing, etc.), don’t do it!
The bottom line as retailers look to position their products, create timely and compelling offers, and deliver on the promise of true omni-channel commerce, is to leverage all insights to streamline back-end processes and simplify front-end interactions. This means chunking down the path to purchase, and looking for ways to present the right product at the right time, offer help (if needed), and make it easy for consumers to finish their journey.
What do you think? Do you buy it?
Last week I gave the closing keynote at IMS San Francisco on the topic of Rich Media, Personalization and Small Data. The event – which brings together top marketers and thought leaders in content marketing, social media and advertising – was a great forum for testing some of my latest thinking on content and scale. And specifically the growing shift from big budget campaigns, long-form video, and big data, to word of mouth viral campaigns, short-form content like vine and snapchat, and small data.
As I shared, this shift impacts (and enables) how marketers can create more effective way to reach and engage customers AND employees, and how they can bring their stories to life. To do so, I argued we need to align around 3 goals:
- Inform – Be HELPFUL! People pay attention if you’re saying something useful or unique – and you reach them when they are thinking about what you are saying,
- Connect – Help customers connect with you and each other…and
- Motivate – The essence of influence is motivating a behavior; in the digital world, content + context drives participation. The ultimate goal of content marketing (and small data) is creating this action or behavior. No participation or action = NO ROI!
With these goals in mind we can map out specific tactics like making video content and your YouTube channel part of your product strategy, and bringing data to where your users are, via mobile apps, social coupons or QR codes.
You can check out my entire presentation and see other examples and takeaways in my SlideShare below. Enjoy!
As social channels continue to feed the big data hype machine, I figured it would be insightful to fire up my favorite social search tool to see which vendors are making the grade (or dominating the conversation) when it comes to social discussions. This post summarizes what I found after a couple evenings of analysis, so it’s not meant to be exhaustive by any stretch, but hopefully provides some interesting insights – and a starting point for further analysis. Thanks for checking it out!
For a first cut, I used Topsy, an excellent search tool we’ve used for social strategy projects at The Pulse, and took a look at mentions of the hashtag #bigdata along with 35 of the top vendors in the space (e.g., #bigdata AND Google) over a 30 day period ending before the end of November, from ALL sources (links, Tweets, Photos, Videos, Experts) on Twitter. Not surprisingly, IBM is dominating the discussion, with over 1000 mentions, followed by EMC (381), SAP (375), Google (355) and Microsoft (310).
Among upstarts, Cloudera was right behind Oracle and HP at 158 mentions, with Splunk (72) and MapR (58) getting their share of social buzz. Interestingly, some much bigger players like Hitachi (only 15 mentions), Xerox (8) and Fujitsu (8) are failing to generate much social chatter related to big data – at least on Twitter.
Here is the full roundup:
To get a better view of social activity weighted by resources I compared the social mentions to the latest vendor data from Wikibon – and more specifically looked at the ‘mentions’ rank vs the revenues rank. So IBM, with the top social mentions AND the top revenue, was right at mid-table (or ‘0’). While standouts (largest difference between social rank and revenue rank – what I’ll call ‘Social IQ’) were QlikTech, Tableau, MapR and Cloudera. Perhaps not a surprise since all are relatively young/small, but well-funded and clearly hitting the social trail big time.
Perhaps a surprise in this cut of the analysis is the strong performance of Microsoft, Oracle, SAP and EMC, showing that all are getting the word out and associating their offering with the big data movement. Note that if a vendor was not included in Wikibon they won’t be in the following chart!
Here’s the full results for the Social IQ of the top big data vendors based on mentions vs revenues rank:
So, who are the ‘social stars’ at this point? Among big companies, IBM, EMC, SAP, Microsoft and Oracle stand out. And among upstarts, clearly QlikTech, Tableau and Cloudera are making the grade.
I’d love to hear your thoughts on other vendors I should include in this study. And please suggest other measures as well for the next cut at the analysis. Thanks again for stopping by!
Large organizations are in love with big data and big analytics. In fact, back in March, IDC forecast that the big data technology and services market is expected to grow from $3.2 billion in 2010 to $16.9 billion in 2015, while it’s been reported that Deloitte estimates the size of the big data market at $1.3-$1.5 billion in 2012. Yet many employees aren’t equipped to harness these insights in their everyday decision making. And perhaps even worse, many executives and boards are still oriented towards an ‘inside’ data view vs customer or employee engagement type data that has increasing value as social and mobile networks take off, as Barry Libert argues.
Meanwhile, in the consumer world, brands like Amazon, Apple and Nike are shifting their own big data engines into high gear to deliver more personalized offers, recommendations and experiences that drive loyalty and sales.
What’s the connection? While companies (and computers!) like big data. Most people only need small data. Not only in terms of what is ‘good enough’ when it comes to the size of the data set. But also in terms of:
- Delivering simple, consumer-style, self-service apps and devices vs. complex toolkits,
- Providing context-driven, highly accurate answers and explanations (note I said answers, not data),
- Applying the latest Responsive Web Design and social marketing techniques to deliver a great experience across all Web-enabled devices and sharing channels.
Google may do this better than anyone currently when it comes to consumer applications. And on the business front, one can argue that Salesforce has done the best job to-date blending enterprise functionality with social insights and Web-style ease of use to create CRM solutions that your typical employee actually wants to use.
Of course other vendors, brands and investors can benefit from this small data approach, if they focus on creating simple, smart, responsive, socially aware tools and solutions.
Who is driving this small data revolution – even if they don’t know it yet? In terms of tools, my list would start with the new generation of speciality social analytics and business intelligence providers like Bluefin Labs, GoodData, NetBase, QlikTech, and Visible Technologies. In future posts I plan to explore these companies and other vendor categories, look at the role of rich media in both creating and delivering insights to the right audience, and highlight organizations like Nike who are leading the way in taking a small, localized view of big data. I look forward to hearing your thoughts and welcome recommendations on who I should spotlight in future posts.
thanks for stopping by!