The Press here in Christchurch this morning had this piece on CRM systems for SME’s. The biggest surprise was that a traditional newspaper was mentioning something as esoteric as CRM but once I got over that I was pleasantly surprised at the level of understanding of the strengths and value of a CRM for small NZ businesses.

The gist of the article was that NZ businesses need to move from being product-centric and become much more customer-centric. This is another way of describing added value and also very much falls within my previous discussions about building customer persona models in order to truly understand the customers of a service or product.

The article also stated that a CRM should not be seen as a bolt on solution for an enterprise but rather become an integral part of the business. And this very nicely dovetails with my perspective about where service and software providers to SME’s need to focus.

Two words spring to mind – integration and partnership. Providers need to integrate various aspects or tools of  a business in a holistic way such that the end result is a seamless process – CRM blends with ERP blends with product development and so on. Partnership is the other strong theme here – no longer should service or software providers see themselves as providing a single occasion service – rather they need to see themselves, and aid the enterprise to see themselves, as an integral partner of the business.

It is for this reason that I believe SaaS will become the pre-eminent delivery model for enterprise solutions in the next few years. And not just because of the cost and deployment benefits – rather SaaS provides a medium whereby the solutions can be attuned and integrated specifically for the business in question, Further SaaS is a much more partnership developing delivery model than traditional purchase/upgrade models.

The challenge here is for SaaS businesses to holistically aggregate the various tools a business requires. This can either be via opening up API’s to allow third party developers to come up with plug in solutions (think the Facebook apps we’ve all seen)  or by a provider going it alone and either acquiring or developing the various tools needed.

It’s time for software entrepreneur’s to think much more strategically and try and develop a model of where they see their particular area of expertise developing and how that integrates with other related areas. It is the linkages between disparate but related solutions that will be the defining element of service provision in the future.

Ben Kepes

Ben Kepes is a technology evangelist, an investor, a commentator and a business adviser. Ben covers the convergence of technology, mobile, ubiquity and agility, all enabled by the Cloud. His areas of interest extend to enterprise software, software integration, financial/accounting software, platforms and infrastructure as well as articulating technology simply for everyday users.

1 Comment
  • Falafulu Fisi |

    Ben, from that article you’ve linked to, it stated:

    Among the big corporates such as the banks and power companies, this has led to an explosion in the market for customer relationship management (CRM) software, data-mining tools, and other essentials of the modern customer-focused enterprise.

    I quoted on the other thread about the Microsoft CRM package , they might throw or bundle in some extra Analytics capability in their tool. I am not sure whether Salesforce use predictive analytics or just the traditional OLAP based traditional business intelligence query or drill down. Predictive analytics is far superior than OLAP drill down business intelligence and CRM vendors that offer this capability get the upper hand in terms of cutting edge functionality as I have stated in the thread for AI. In fact Predictive analytics is based mainly on statistics and data-mining, where majority of algorithms for data-mining do come from the discipline of Machine Learning, a sub-branch of AI. See, Ben, this is exactly what I emphasized in posted on the other thread about AI. The adoption of Predictive analytics, be it a CRM application, Web-Marketing, Online Recommendation such as Amazon, (basically AI-based technology) ,etc, in todays corporate management is exploding. This is what I see today. A CRM vendor that doesn’t jump the bandwagon and adopt Predictive analytics as part of their tools functionalities, would find themselves lose market to vendors that do have them. This was why I posted on the other thread and made an assertion that Microsoft might bundle Predictive analytics in with their CRM product. I don’t know about Salesforce, but I suspect that their tool hasn’t implemented any Predictive analytics capability. Perhaps, they only have OLAP, but I am not sure. If they don’t see the tide’s coming, they will sub-merge in the competition to vendors such as Microsoft. I have to say that the Microsoft Datamining group R&D (Microsoft Asia Divsion) is impressive. New algorithms, and also improved versions (low error) of old algorithms have been published in a number of international datamining journals. I have made contact with this group a number of times in the past to request copies of their papers, since I don’t subscribed to any paid journals, and also to clarify certain bits of the derivation of their algorithms in order for me to correctly implement them.

    I am involved in drafting of the official Java Data Mining standards for the Java technology version 2.0 (JDM 2.0) and we will have a final release to the general public in the next 2 months.

    I have no clue to how would data-mining would work out in SaaS platform, since data-mining is memory intensive (high-speed number-crunching) that requires super-computers I guess. Amazon is an example. The customer transaction data is so huge that they parallel computing. The recommendation that one sees when they click on an Amazon link or browse thru their website, is not a live retrieval. The data is regularly computed offline, then deployed live with recommendation such as:

    Customers who bought item A also bought item B


    Customers who bought item A also looked at item B, etc.

    This makes online customers want to buy more than the one item they went in to Amazon to look for, and that is actually the case, people ended up buying more than one item. A very good automated online cross-sell & up-sell. See AI works Ben. This process of off-line data-mining (batch processing) is often repeated regularly (say, every 2 days or so), because the recent data (online customers buying behavior) must be included and not heavily rely on old data. THIS is how GOOGLE does its datamining as well. The ranking of pages is computed off-line using their PageRank algrorithm by a clusters of super-computers, and the results , are then deployed live online. They also update their results with new links that their crawlers has just identified. I think that the update is done every 2 or 3 days (may be daily as I am not sure).

    The difference here, is that Amazon has only one huge dataset in comparison to SaaS based CRM with datamining capability, there would be 10,000 or more huge databases to mine off-line before deploying the mining models live online. This requires super-computing capability on the part of the SaaS vendor.

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