Techaisle Blog

Insightful research, flexible data, and deep analysis by a global SMB IT Market Research and Industry Analyst organization dedicated to tracking the Future of SMBs and Channels.

SMB analytics begins with cloud and provides answers to business issues

Techaisle recently analyzed 1,116 survey responses that provide insights needed to build and execute on analytics strategies for targeting the small and midmarket customer segments.

SMBs are prioritizing a wide range of improved outcomes within their businesses: improvement within existing operations and processes, expansion of the customer base, profitability, creation and accelerated delivery of new offerings, reduced cost, and enhanced ability to manage the unknown. Remarkably, each of the top SMB business issues can be addressed with analytics solutions – and indeed, SMBs are using analytics to address each today. Overall, SMB analytics investments are being driven primarily by productivity and process improvements with the top two reasons for SMB investments in analytics solutions as increased productivity and improved processes.

Regardless of the business issue, analytics provides an answer. And SMB analytics begins with cloud. More than 50% of both small and midmarket businesses consider cloud to be an essential analytics technology.

Continue reading
451 Hits

85 percent of omni-channel SMBs are using analytics solutions

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.  

Continue reading
1226 Hits

Big Data in the Cloud - an ideal solution for SMB banks

Wall Street Journal carried an article on how regulatory burdens had made community banks “too small to succeed” despite performing better than larger banks regardless of being better capitalized and having lower default rates.

The advent of cloud technologies has the potential to change WSJ’s dire prognosis.

Cloud may have first been introduced as a means of reducing CAPEX and/or overall IT costs, but today, it is viewed by small and midmarket businesses as a means of increasing business agility and of introducing capabilities that would have been cost or time-prohibitive to deploy on traditional technology. Complementary to cloud, big data analytics presents the possibilities of connecting together a variety of data sets from disconnected sources to produce business insights whether for increasing sales, improving products or detecting fraud. SMB banks are a specific segment of SMBs who can derive the benefits of customer insight while meeting their mandatory regulatory requirements.

Techaisle classifies SMB banks as those below $10B in assets and medium sized banks as those between $10-100B in assets. SMB banks below $10B in assets often called “community banks” play a very important role in the ecosystem of SMB businesses. Although FDIC, OCC and FRB have different definitions of community banks, it is important to note that these smaller banks not only accounted for nearly half of the total of about $600B outstanding small business loans at the end of 2014 but also play a disproportionately major role in the $1.8 trillion residential mortgage origination market.

Unlike large banks, SMB banks are characterized by George Bailey in “It’s a Wonderful Life”. These banks usually have keen insights on their customers based on personal relationships and carry a tremendous amount of tribal knowledge about their customers which they use to make business decisions. While this corpus of knowledge may not be codified it does make a difference in their business operations. But is that enough in today’s hyper-competitive economy where the relationship is being increasingly controlled and dictated by customers?

Then there is another question, are these smaller banks doing enough to detect fraud? High-risk businesses that have been denied services by large banks tend to move their business to smaller banks who are less equipped to analyze these risks. These smaller banks are unknowingly exposing themselves to fraud as well as compliance risk. Regulations are agnostic to bank size and equally unforgiving of SMB banks as they are of large banks. A cloud-based analytics solution may just be the recipe for success for the smaller banks. In fact, these banks are no different than midmarket businesses (or even small businesses) in their objectives of adopting big data.

techaisle-top-business-drivers-for-smb-big-data-adoption

Monitoring, analyzing and reporting very large volumes of data are typically the largest components of regulatory costs for SMB banks. Many often use antiquated technology and manual processes to manage their compliance requirements. Banks that are able to automate the process of managing data for regulatory requirements can have the added benefit of getting a unique view of their customers through one single technology solution.

According to Shirish Netke CEO, Amberoon, a provider of Big Data solutions for banks, “A lot of the data that is required for regulatory compliance can also be easily parlayed into getting insights on the banks customers and improving business”. Amberoon has built a banking solution for SMB banks provisioned on the IBM SoftLayer cloud.

Security & privacy (especially FFIEC requirements), traditional inhibitors of cloud adoption, are a legitimate concern for banks. After all, banks are the custodians of individual’s money, facilitators of trade and commerce and life-line of businesses. However, it may be argued that these inhibitors have already been successfully addressed by service bureaus. A very large percent of SMB banks outsource their core banking system to service providers such as Fiserv and FIS Global who have built very large scalable service bureaus with the economies of scale afforded by centralizing technology resources.

Aptly put by Noor Menai, CEO of CTBC Bank. “Outsourced technology services are nothing new in the banking industry. There is a compelling reason to use big data technologies in banks if they are available at an affordable cost in a secure manner. Cloud has the potential to provide both”.

Big data analytics in the cloud can be an execution advantage, and may even propel the SMB banks to leap ahead of larger banks on solutions that address both regulatory necessities as well as gain competitive edge from customer analytics. Historically, Siebel, an on-premise solution, was usually deployed in large enterprises and was out of reach for smaller businesses. Salesforce, a cloud solution, changed the perception, adoption, usage, affordability and provided immediate business outcomes. Today Salesforce is used by both SMBs as well as large enterprises.

Combining the benefits of cloud with the advantages of big data analytics may just be the prescription that SMB banks need for business growth (cross-selling, upselling services), meeting regulatory requirements such as KYC/AML/BSA and deep-diving into fraud detection.

One should also not forget that big data implementations require a unique combination of technical, operational and business skills to be used in a sustained manner. Needless to say, these skills are in short-supply but affordable by deep-pocketed larger banks. While some smaller banks including community banks can spend the money to experiment with big data pilots, they do not have the capacity to go through expensive iterations to get it right. While larger banks have the luxury of choosing between on-premise big data versus cloud big data, for smaller banks the choice could very well be between either doing big data on the cloud or perhaps not doing it at all. The remaining question therefore is – which big data cloud supplier will take the lead in educating, evangelizing and then executing on the needs of SMB banks.

4576 Hits
0 Comments

Path to Big Data Adoption Success: Mid-market and SMBs

Techaisle's Big Data study of 3,360 businesses shows that mid-market businesses typically started their big data journey in one of four ways. However, the highest success rate (determined by reaching a successful implementation of a big data project within six months of initiation) was achieved when an external consultant or organization was brought in to develop proof of concept, advice on database architecture and ultimately develop the big data analytics solution.

techaisle-smb-big-data-adoption-path


Once a decision was made to embark on a big data deployment project, the mid-market organization tended to quickly align behind the initiative. They did realize that big data was not a typical cloud application deployment where independent department purchases could be made, nor was it infrastructure deployment where only IT could be involved. Big data required a new type of alignment between business heads, namely, Marketing, Finance, IT and a completely new set of players known as data scientists or data analysts.

Study shows that businesses are moving from “whack-a-mole” analytics to “business perspectives” to get newer insights into their operations and better knowledge about their customers as they rethink their marketing strategies because mobility, social media, and other transactional services have increased the number avenues for connections with their customers. There are many different tactical objectives for deploying big data projects but the top among them are sentiment monitoring, generating new revenue streams & improving predictive analytics. And businesses are expecting some clear cut benefits from big data analytics such as increased sales, more efficient operations, improved Customer service.

 
7440 Hits
1 Comment

Search Blogs

Find Research

SMB Data You Can Rely On | Analysis You Can Act Upon

Techaisle - TA