Techaisle Blog

Intrinsic to positioning any IT-enabled solution is an understanding of the benefits that the customer anticipates obtaining from deployment of the technology. Buyers need to understand how the solution helps them to increase revenues, cut costs, improve efficiency or otherwise enhance shareholder value; vendors need to be able to position their offerings as a means to achieving these objectives.

While there is a close relationship between “analytics” and “Big Data” – and they are often conflated in the press – the two technologies follow somewhat different paths into SMB user environments. Techaisle research has found that analytics solutions tend to be driven by BDMs – business users looking for better ways of approaching high-priority business issues. In some cases, this requires access to vast quantities of high-velocity, variegated sources, which in turn demands a Big Data solution – but in contrast to analytics adoption, Big Data initiatives rely heavily on IT for implementation and ongoing management, and represents a solution area that requires collaboration between BDMs and ITDMs.

While SMB Big Data buyers view support for (predictive) analytics as their top acquisition driver, they also have distinct needs and preferences that suppliers must consider in building a sales and marketing strategy.

One interesting observation contained within Techaisle’s 2016 SMB & Midmarket Analytics Adoption survey results is the relationship between sales channel and analytics strategy. The survey of 1,116 US SMBs found that a higher percentage of businesses with an omni-channel approach that includes both online and offline sales channels are using analytics than those relying entirely on either online or offline sales. In fact, overall, 85% of omni-channel SMBs are using analytics and 38% are using big data solutions. On the planned side of the equation, another 46% of omni-channel SMBs are investigating use of big data technologies. Even the average spending on analytics by omni-channel SMBs is 3X that of eCommerce only SMBs and 6X of those that do not sell online.

Data illustrates that nearly 60% of SMBs (and almost three-quarters of midmarket firms) employing an omni-channel strategy are already using analytics to track website hits – a rate that is higher than for firms using ecommerce-only, and much higher than for firms that do not use online sales.

Another set of data adds context to this focus on website tracking. Omni-channel businesses tend not to be using particularly advanced approaches to analytics:

• 39% use “descriptive” analytics, and
• 30% have deployed “predictive” or “prescriptive” analytics.

However, omni-channel firms do tend to have some type of strategy – only 5% report that their use of analytics is ad hoc, vs. 13% of ecommerce-only firms and 18% of firms with no online sales.

The current analytics solution deployment & usage differs greatly from future plans within the omni-channel SMBs.  

In today’s SMB market, it is critical for vendors to build detailed understanding of the small and midmarket segments, and to align resources and strategies with requirements as SMBs move from initial experimentation with sophisticated solutions towards mass-market adoption.

In the report, Analytics and Big Data in the US SMB market, Techaisle analyzes over 1100 survey responses to provide the insight needed to build and execute on analytics and big data solution strategies for the small and midmarket customer segments. Techaisle’s deep understanding of SMB IT and business requirements enables vendors to understand the ‘why’ and ‘when’ of solution adoption, current and planned approaches to solution use, the benefits that drive user investments, and key issues in aligning with buyers and building and intercepting demand.

Highlights of data presented in this report include:

Techaisle’s quantitative study (survey of nearly 900 SMBs) on SMB & Midmarket Big Data Adoption and Trends shows that 7 percent of small businesses and 20 percent of midmarket businesses are currently using Big Data solutions and that another 17 percent & 38 percent respectively are planning to adopt within the 1-2 years. These businesses are looking at a big data solution from 3 perspectives:

“First, what are the organizational needs, second, what could be served as a solution and, third, what could be the best combination of the tools and technologies available today which will provide value add. Based on all one should decide on a solution because the Big Data space is very enormous and could be applied for any domain,” aptly quoted by CIO of a midmarket firm who has successfully implemented big data solutions in his organization.

Common findings that run through corresponding depth interviews (over 60 interviews conducted globally) conducted by Techaisle, Insights from the Trenches of SMB Big Data Implementers, are:

• PoC – more is better, timing is of essence
• Cost efficiencies of Hadoop, especially Cloudera
• Plethora of tools deployment – emergence of Spark and Flume
• On-premise only – now and the future
• Must conduct skills training and gap analysis
• Lessons learned – not to underestimate complexity but uniform voice – go for it

The promise of superior data-driven decision making is motivating 24 percent of US small businesses (1-99 employees) and 58 percent of midmarket businesses (100-999 employees) to invest in Big Data technology.

In addition, the possibility of analyzing a variety of data producing action-driven business insights is too big to ignore for midmarket businesses. This represents a sizable opportunity considering that the segment is relatively new, it requires a certain level of IT sophistication and a history in linear investment in information technology enablers to be successful.

Specifically, midmarket attitude towards big data has transitioned from “over-hype” to “must-have” technology with the increase in employee size. Only 11 percent of midmarket businesses consider big data to be an over hype suggesting that it has crossed the tipping point faster than similar sentiments for cloud adoption at its introduction. However, nearly one-fourth of lower mid-market businesses still consider it to be over-hyped yet 29 percent think that it will be an important part of their business decision making process.

Nevertheless, SMBs face many challenges in implementing big data solutions.

There are many different tactical objectives for deploying big data projects and SMBs are expecting some clear cut benefits from big data analytics such as increased sales, more efficient operations, and improved customer service.

CRM solutions had first established the analytics for analyzing customer data but the data was mostly two-way transactional data. This changed when customers began visiting business websites to explore, browse and perhaps make purchases thus leaving behind a trail of information. IT vendors and mid-market businesses figured out the need to analyze the data and combine it with transactional information.

However, everything changed with the onset of social media, blogs, forums and opinion platforms where the identification of false positives and negatives became difficult and knowledge about the customer and resulting segmentation became an inaccurate undertaking. Big data analytics presents the possibilities of connecting together a variety of data sets from disconnected sources to produce business insights whether for generating sales, improving products or detecting fraud. It is therefore not surprising that globally SMBs and midmarket businesses are turning towards big data analytics to analyze social media data, web data, customer and sales data along with click-stream machine generated data and even communications data in the form of emails, chat, voicemails.