What is the future of CRM analytics? What upcoming problems might exist? What aspects might be in decline?

 

Source: (Playbuzz.com, 2016)

So what is the future of CRM?

In the past, the meaning of CRM for everyone was sales force automation only. Then, as things were moving forward, marketing automation was added to that functionality. All that wasn’t there was actually social channel incorporation only.

Before we speak about the future, let’s take a look at what we have in hand right now.

At the moment, CRM is mostly focused on internal business management practices such as customer information management, market strategy design (based on sales) and basic customer related communications. They are designed to increase process efficiency and reduce operational cost by analyzing sales and in turn influencing business operations. But somehow, organizations still fail to inspire customers enough to improve and retain relationships. With social media advancements, a communication evolution followed. This communication evolution is going to lead us to the future.

In the future, with social CRM will help organizations be better customer oriented. The future goal of CRM will be to improve communication between an organization and its customers. It will be an application to know and explore consumer needs. In a recent case study sponsored by SAP on six innovative companies, namely e de Transport de Montreal, Lenovo, Australia and New Zealand Banking Group, ARI, coop@home and CEMEX, studies revealed that “Businesses need to provide an unbroken and highly relevant conversation across channels, responding to and even anticipating customers’ ever- evolving needs. In today’s terms, this is known as ‘customer engagement’.” (SAP, 2015) This shows a changing trend in needs of the customers. Better customer engagement will also help build tailored strategies that each customer would desire. Speaking of customer engagement, it is exactly where CRM is headed towards.

In terms of data science, the biggest difference will be changes in research objectives. Instead of concentrating just on sales data, consumer behavior and engagement will be the new areas of concentration. For example, a future CRM system would be able to discover customer demands based on onsite behavior or targeted personalized recommendations and promotions.

 

Source: (act-on.com, 2016)

Upcoming Challenges to CRM and data science

The future will challenge data science for better or for worse in two major ways being, data and technologies.

Scalability

Scalability will continue to challenge data analysts. With more customer interaction, data volumes are at an all-time high and will still continue to increase. Although, CRM has transferred from sales driven to a customer centric model, strong data analysis plays important role to provide insights about customers. “During the next eight years, the amount of digital data produced will exceed 40 zettabytes, which is the equivalent of 5,200 GB of data for every man, woman and child on Earth, according to an updated Digital Universe study released today.” (Mearian, 2012)

Technology

The technological challenges that exist in data science will hinder CRM transition as well, especially dealing with poor quality data. Large and noisy datasets will definitely add to difficulties. Also, having an omni-channel platform presence definitely helps organizations engage with their consumers but it adds to difficulties in managing consumer data and getting better insights from it.

All in all, if we think about what might be in decline when talking about the future of CRM and data science, then the first and last thing that comes to mind is non-customer oriented traditional practices. This is because, all the decisions that CRM will help aid stakeholders in making can be data driven and concrete. 

Interesting reads for the literary inclined geeks and references

• Cdn.playbuzz.com. (2016). Playbuzz.com. [online] Available at: http://cdn.playbuzz.com/cdn/c9c1b883-9a63-4467-8830-b083f322b786/b1853fe9-7972-4fff-8740-dfb8ea7c3213_560_420.jpg [Accessed 13 Jun. 2016].
• Evergage. (2014). The CRM of the Future: Data Curation and Predictive Analytics. [online] Available at: http://www.evergage.com/blog/crm-future-data-curation-and-predictive-analytics/ [Accessed 13 Jun. 2016].
• Forbes.com. (2015). Forbes Insights: Customer Engagement. [online] Available at: http://www.forbes.com/forbesinsights/sap_customer_engagement/index.html [Accessed 11 Jun. 2016].
• Act-on.com. (2015). [online] Available at: https://www.act-on.com/blog/wp-content/uploads/2015/03/Customer-Engagement.jpg [Accessed 13 Jun. 2016].
• French, T., LaBerge, L. and Magill, P. (2011). We’re all marketers now. [online] McKinsey & Company. Available at: http://www.mckinsey.com/business-functions/marketing-and-sales/our-insights/were-all-marketers-now [Accessed 12 Jun. 2016].
• Mearian, L. (2012). By 2020, there will be 5,200 GB of data for every person on Earth. [online] Computerworld. Available at: http://www.computerworld.com/article/2493701/data-center/by-2020--there-will-be-5-200-gb-of-data-for-every-person-on-earth.html [Accessed 12 Jun. 2016].
• Schaeffer, C. (2016). The Future of CRM Software. [online] Crmsearch.com. Available at: http://www.crmsearch.com/future-of-crm.php [Accessed 13 Jun. 2016].

Ongoing trends and techniques in CRM analytics and the challenges faced

 

 

Source: (raconteur.net, 2016)

Ongoing trends and cutting-edge techniques in CRM software

Now that we know what CRM software is and what it is capable of, let’s take a deeper look into ongoing trends in the market and the cutting-edge technology that is being used to maximise CRM software’s potential.

Before we go any further, let me briefly introduce an ongoing CRM related trend floating in the market these days. Big data CRM – As the name suggests, Big Data CRM basically refers to the practise of combining big data with a company’s CRM processes. This essentially means that the software uses data that exists outside of the ecosystem of the company, such as social media etc. It adds to the value of older CRM practises by finding patterns in this data that can be used to exploit newer sales opportunities and help in adjustment of existent product and service offerings.

“Combining big data with other CRM data can improve customer analysis and lead to predictive modeling and other practices.” (Rouse, 2015)

Ever since the ‘big-data’ buzzwords have been attached with CRM, cutting-edge technology has been aligned with this type software to maximise its potential and deliver the best possible results.

“CRM analytics can range from being as simple as query and reporting capabilities to sophisticated data mining and predictive modeling over large quantities of data.” (Schantz, 2010)

Key success factors of successful CRM analytics is based on strong data warehousing capabilities including consolidation, cleaning and formatting and also on ALL customer touch points to create a holistic view of the customer and their purchasing habits.

From multi-channel to omni-channel -

In order to keep up with changing trends, companies have now created their presence on social media, SMS, video and live chat etc and other platforms to keep in touch with their customers.

Big data CRM analytics software helps keep the stakeholders informed of customer decisions and interaction patterns in order to maximise efficiency.

Challenges faced in using cutting-edge techniques and technologies

Admittedly, big data provides competitive and intelligent insights on customers. With the increases in data size, larger data noise became a new challenge for CRM analytics to handle. For instance, if I use my Amazon account to buy a couple of fiction books for my friend, then, I start to receive recommendations like other fiction books and movies. But it was only a time transaction that I am making. And actually, if it weren’t for her, I would not purchase any fictions for myself. Or maybe, I have 3 different accounts on Ebay.com and I am making different types of transactions from different accounts. These scenarios definitely add to difficulties in CRM analytics.

We enjoy the flexibility brought by omnichannel applications and ofcourse cloud solutions.  But, although the external picture with using omnichannels is wonderful, data transformation and integration from different platforms is hard for CRM companies. Customer’s usage of an application changes from one channel to another also at times. Multi data silos makes the process much more complicated than it already is. These channel changes are not limited to devices. Some of the business might includes social media and video chat. Some might supports four or five channels. The burden is heavier for analytics to collect and process data.

There will always be challenges and limitations on a cutting-edge technology. But people always find solutions to cope with issues. Similarly, data scientists will work out solutions for big data CRM analytics and bring better results to the table for their clients.

Just to keep you geeks up to date with the latest technological trends in CRM: IoT cloud and Marketing cloud integration

“A Microsoft-Salesforce partnership focused on interoperability between the two companies' products signals the push to make device data available and actionable.” (Ehrens, 2015)

This would help stakeholders gain better insights and aligns with the above mentioned success factor of organisations taking note of ALL customer touch points.

Interesting reads for the literary inclined geeks and references

• Ehrens, T. (2015). Emerging CRM technologies took center stage in 2015. [online] SearchCRM. Available at: http://searchcrm.techtarget.com/news/4500269181/Emerging-CRM-technologies-took-center-stage-in-2015 [Accessed 4 Jun. 2016].
• Milletti, U. (2015). The Enemy of Data Science: Noisy Signals in the Enterprise. [online] 1to1media. Available at: http://www.1to1media.com/view.aspx?docid=35392 [Accessed 4 Jun. 2016].
• Nicastro, D. (2014). Mobile, Social, Big Data Create 'Perfect CRM Storm'. [online] CMSWire.com. Available at: http://www.cmswire.com/cms/customer-experience/mobile-social-big-data-create-perfect-crm-storm-025811.php [Accessed 4 Jun. 2016].
• raconteur.net, (2016). Landing image. [image] Available at: http://raconteur.net/public/img/articles/2013/09/Report-Landing-Page-Main-Image-Big-Data.jpg [Accessed 5 Jun. 2016].
• Rouse, M. (2015). What is big data CRM (big data customer relationship management)? - Definition from WhatIs.com. [online] SearchCRM. Available at: http://searchcrm.techtarget.com/definition/big-data-CRM-big-data-customer-relationship-management [Accessed 4 Jun. 2016].
• Schantz, N. (2010). The difference between CRM analytics and traditional data mining. [online] SearchCRM. Available at: http://searchcrm.techtarget.com/answer/The-difference-between-CRM-analytics-and-traditional-data-mining [Accessed 4 Jun. 2016].
• Smith, A. (2016). Multimedia-based multichannel CRM still faces uphill battle. [online] SearchCRM. Available at: http://searchcrm.techtarget.com/feature/Multimedia-based-multichannel-CRM-still-faces-uphill-battle [Accessed 4 Jun. 2016].

Who are active users of CRM Software? What problems does effective CRM Software try to solve? What are the challenges faced in finding solutions to those problems?

Who are active users of CRM Software?

The real question is who can use CRM software?

The answer to that question is very simple. “Any business with customers would use CRM!” (Worketc, 2016)

The above includes businesses that are trying to;

↑ Increase efficiency of sales

↑ Improve marketing practices

↑ Generating quotes and invoices efficiently

↑ Improve customer care by showing that customers are high priority

↑ Increase overall efficiency of the business by improving internal processes

In a nutshell, any organisation with sales, marketing and accounting departments would use CRM software.

What problems does effective CRM Software try to solve?

What problems can CRM Software solve for you and your business? Why should you invest in CRM software?

CRM software can help you address numerous problems that you might be experiencing in your business. Some of the most important   problems are;

↓ “Customer feedback isn’t being recorded or used.” (Davey, 2015).

↓ Your marketing messages aren’t as effective as they can be.

↓ Client information is not being managed properly between stakeholders.

↓ Lack of centralised customer knowledge

↓ “Lack of customer issue / resolution tracking system.” (Successwithcrm, 2016)

                                                                    Source: CRMnext.com, 2016

What are the challenges faced in finding solutions to problems?

The challenges faced in finding CRM solutions can be divided among four major entities at your organsation

• Business

“CRM strategy has contributed to 18% of CRM failure.” (Band, 2012) Poorly designed business requirements, wrong methodologies and failure to match business requirements are the main reasons behind this phenomenon. Business is not constant. It is likely to change. The ever-changing key stakeholders and their business objectives have to be considered while deploying a CRM system. Undoubtedly, it is hard to find CRM solutions.

Cost is another consideration. CRM customers have to strike a balance between functions and cost. Don’t let CRM become a burden on your business!

• Employees

For the deployment of any new system, training has to be provided. If an organisation’s staff has a negative attitude towards the system, the company is bound to face difficulties in deploying it. Moreover, if the CRM’s ways and method are different from the business culture of the organisation and if the change in the business processes is not managed properly, there will be threats to successful deployment of CRM.

• Technology

Most common technical challenges are integrity issues. First, some companies would like to integrate new software with their legacy system. However, the approaches that two different CRM vendors take might be different from each other. Also, Data migration could be difficult too. Besides, some newer CRM software connects with emails, calendars and other related systems,but all those features might not be supported by software currently in use.

• Security

Nowadays, information is the most valuable asset for any business. CRM records customer and sales details. Therefore, security is one of CRM customers’ biggest concerns. Especially to keep in mind that most of the CRM providers have adopted cloud for more scalable web-based services. When data is accessed remotely via Internet, information is more vulnerable to security threats. Hackers are geniuses! CRM service providers have to keep up with the new technologies and release patches.

Interesting reads for the literary inclined geeks and references

• Band, W. (2016). William Band's Blog. [online] Blogs.forrester.com. Available at: http://blogs.forrester.com/william_band/12-03-01-dont_let_crm_pitfalls_trip_you_up [Accessed 29 May 2016].
• Davey, N. (2015). 3 problems every B2B brand solves with CRM. [online] The Future of Customer Engagement and Commerce. Available at: http://www.the-future-of-commerce.com/2015/08/03/crm-b2b-trends/ [Accessed 28 May 2016].
• Fpb.org. (2016). Forum Private Business. [online] Available at: https://www.fpb.org/business-support/ten-problems-solved-using-crm [Accessed 29 May 2016].
• Fuke, I. (2015). 15 Practical Challenges in CRM Implementation. [online] SimpleCRM Blogs. Available at: http://www.simplecrm.com.sg/blog/15-practical-challenges-in-crm-implementation/ [Accessed 29 May 2016].
• Schultz, P. (2016). Advantages and Disadvantages of CRM Software. [online] Marketingweekly.com. Available at: http://www.marketingweekly.com/crm/advantages-and-disadvantages-of-crm-software/?mode=featured [Accessed 29 May 2016].
• Sites.google.com. (2016). Challenges of CRM - Customer Relation Management (CRM) Systems. [online] Available at: https://sites.google.com/a/siena.edu/customer-relation-management-crm-systems/challenges-of-crm [Accessed 29 May 2016].
• Worketc.com. (2016). Part 2: Who actually uses CRM Software?. [online] Available at: https://www.worketc.com/crm_101/part_2_who_actually_uses_crm/ [Accessed 28 May 2016].
• CRMNext, (2016). CRM Strategies | CRM Challenges. [image] Available at: http://www.crmnext.com/media/1551/cloud-crm-challenges.png [Accessed 30 May 2016].

Data science and customer relationship management

                                                                                               Source: Salesnet.com, 2016

What is CRM?

CRM stands for Customer Relationship Management. Basically, it can be referred to any method, tool or technology that helps us improve business relationships with customers through the customer lifecycle.

Currently, software is capable of managing CRM for us. This software automates sales, customer service and marketing processes.

When a customer arrives at the counter, CRM software collects their purchase record, contact information and etc. Some software is even capable of storing customer information on Cloud. When an employee is sick, his or her colleagues will still easily access to customer information.

 

What are the functions of CRM software?

                                                                     Source: Author

• Sales: CRM software not only collects the basic order history and customer details, but also automatically tracks order status, creates invoices etc. Using data science, this software can provide sales forecast services as well which is valuable for companies to enhance their supply chains.

•  Customer Service: CRM software integrates all sorts of information within one system. For customer service, it reduces redundancy and improves customer experience. The communication between a customer and the company is not restricted to a specific employee any more. Keeping information privileges in mind, any staff could know past communications to improve customer familiarity. Moreover, CRM is competent to track the performance of their employees. Sales representatives could view their sale numbers and incentives on this system.

• Marketing: Along with customer services record, stakeholders can know and understand the patterns of the customer and sales. Marketing plans can be optimized to be targeted better.
  For example, a supermarket gives each promotion a unique code. With the CRM, the supermarket will have the knowledge of what promotions are more compelling to customers. They begin to use the compelling promotions in their marketing and attract more clients since then.
  

 

Data analysis in CRM Software

How does the software know the answer to all our sales needs? How is it able to project estimated long and short term sales and performance forecasts?

Two words, Data Analysis!

A CRM software performs statistical analysis on large amounts of data to achieve all of the above mentioned functions.  

For example, a leading player in this domain like Salesforce owns proprietary predictive models that use customer behavioural data to boost sales by helping optimise advertisements and to predict sales accordingly.

 

Why should you care?

It’s very simple! Data analysis and CRM can assist the stakeholders with the functions mentioned below.

↑     Increase sales by optimising sale closing process.

↑     Expand sales base by assisting stakeholders to forecast the sales of a product in a new geographic location. 

↑     Achieve broader insights about the current customer base.

↑     Manage current orders.


Interesting reads for the literary inclined geeks and other references

• Salesnet.com. (2016). [online] Available at: https://www.salesnet.com/wp-content/uploads/2016/01/Dollarphotoclub_92112876.jpg [Accessed 23 May 2016].

• SearchCRM. (2016). What is customer relationship management (CRM) ? - Definition from WhatIs.com. [online] Available at: http://searchcrm.techtarget.com/definition/CRM [Accessed 23 May 2016].

• Angeles, S. (2016). Choosing a CRM Software: A Buyer's Guide. [online] Business news daily. Available at: http://www.businessnewsdaily.com/7838-choosing-crm-software.html [Accessed 22 May 2016].