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How to choose salesforce consulting services partner

Originally Posted here- How to choose Salesforce consulting services partner

Choosing the right salesforce consulting services provider is vital in getting the best out of your Salesforce CRM. A good salesforce consulting partner can help you from salesforce implementation to maintaining and optimizing your salesforce platform, continuously.

The selection of the right salesforce consulting services partner is very significant as it can affect your business directly, the chosen salesforce consultant has an impact on your salesforce CRM functioning and CRM directly affects your business. Thus a good salesforce consultant is important for the efficient functioning of your business.

Things to analyze before starting the process of salesforce consulting services provider -

Know your Industry- Just knowing the name of your industry is not enough, you must be completely aware of the needs and requirements of your industry and what can be upcoming trends in your industry. Knowing how other players & your competitors from the same industry are using the “salesforce consulting services providers”  will also help you in formulating your salesforce CRM strategy and also in choosing the right salesforce consultant.

Your company size- If you are a small organization then salesforce service consultants who have been involved with large organizations might not do justice for you; vice versa is equally true.  

What is your goal- Clearly define your Salesforce CRM goals, whether you need an operational CRM for needs like sales, marketing or services or you need analytical CRM or collaborative CRM? Knowing your needs will help you in choosing the salesforce consultant who has relevant experience.  

Engagement model- You must also introspect whether you need an employee or you need an outsourced salesforce consulting services provider. Normally if you are a software technology company then hiring a full-time employee is a better choice but if you are not a software company then outsourced salesforce consultants can be a better choice. At times this also depends on the size of a company; if you are a non-software company but a big organization that already has a dedicated software team then hiring a full-time salesforce consultant can be a good choice. However, there is no thumb rule to choose between a full-time employee vs outsourced salesforce consulting service provider. One needs to assess their needs and decide accordingly.

One time or ongoing support - You also need to assess, whether you need one-time support from your salesforce consultant or you need ongoing support, based on the selection of your need of salesforce consultant may differ, as at times the best available salesforce consultant might not be available for a long term commitment.

What is your budget- Needless to say, that budget is an important criterion for selection of a salesforce consultant. Based on your budget you have to select the best available salesforce consultant. Depending on your budget you can also decide between onsite or offshore salesforce consulting service providers. The salesforce consultant rates in countries like the USA, UK, Australia may vary between US$70/hr to US250/hr. However one can get an equally good salesforce consultant in India between US$15/hr to US$35/hr.  

Check what you need - Admin/consultant/ Developer - Many people may consider it as very basic information but it's very important to understand. One person may have all the capabilities but it's not necessary.  Salesforce admin, salesforce consultancy and salesforce development are three different skills and it is not necessary that one resource will be skilled in all three of them. You must know what is your need and what is the expertise & skills of resources that you are considering.

Analyze what integrations & bespoke development are required by your CRM - Your salesforce CRM may also be in need to be integrated with tools outside or inside of salesforce ecosystem, there may also be need of bespoke development to achieve certain functionalities, thus it is important that your chosen salesforce consultant is able to consult you and do the development if required for integration and bespoke salesforce development.

Make a shortlist of available salesforce consulting services provider-

Specialization, certificates, and expertise of salesforce consultant: Checking the expertise and capabilities of prospective Salesforce consulting partner is an obvious step and checking out what certificates consultant has is a vital step but not sufficient. More than certificates of probable salesforce consultant, one should focus on understanding what past experience the consultant has, certifications are good but more than certifications; it's the relevant past experience of a salesforce consultant that matters.

Concentrate on salesforce consultant’s capabilities more than rates: Everybody wants to save money and it's true that you should also try and get the salesforce consultant that offers you better rates but remember a wrong salesforce consultant can negatively affect your business, thus first criteria should be capabilities and than filter according to the rates of consultants.  

Check business references of all the salesforce consultants: This is very important, ask for business references from your prospective salesforce consultants, talk to their business references, try to understand why they like or did not like a particular salesforce consultant.

Compatibility with salesforce consultant: Talk to all the salesforce consulting service providers, understand their way of working, explaining to them what do you expect from them, know their approach and check your compatibility with the probable list of salesforce consultant, salesforce consultant can be good but might not be compatible with you. So for the success of your salesforce CRM, your compatibility with your chosen salesforce consulting services provider is important.

Make a circumspect start with the chosen salesforce consulting services consultant -

Have the necessary NDA & SLA in place: Get the NDA and other intellectual right protective documents signed right at the start of your communication. Sign a service level agreement that clearly defines each and everything. Signing the necessary documents is very important.  

Start slow: Before entering into a long term agreement, start with a small piece of work that will help you in not only understanding the capabilities of a salesforce consultant but also in checking your compatibility with your selection.

Give your time/ teach your salesforce consultant: Only selecting the right salesforce consultant is not enough, you need to continuously talk to the consultant and teach them about what is your business and what you want to achieve, salesforce consulting service provider should be completely aware of your priorities and goals.

Check progress: You must clearly define milestones and checkpoints to check the progress and quality of work, doing this will help you in getting a high-quality output in a timely manner.

Be clear about your working style: Make your salesforce service provider aware of your working style so that your salesforce consulting partner should know how to communicate with you and what are your likes and dislikes. In this way, a salesforce consultant can proactively do what you want from him/her.

Choosing a services provider is like marrying someone (well, not literally ) and that is equally true when it comes to choosing your salesforce consulting service provider.Your choice can make you happy or sad.

I hope the suggestions shared with you in this article will help you get the right salesforce consulting services provider for your salesforce CRM strategy.

At Emorphis Technologies, we specialize in providing salesforce consulting services and if you have any further questions we would be happy to talk to you and provide you the right answers.

Abhinav Shrivastava

abhinav@emorphis.com Originally Posted here- How to choose Salesforce consulting services partner

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FinTech Application Development: How Machine Learning is Making it Better.

With rapid and massive technological advancements in fintech application development ecosystem; the finance sector can easily be considered as one of the largest adopters of technology. Now Machine learning is now taking these advancements to the next level.

Given the quantifiable nature of financial systems, accuracy in financial records and even the higher capacity of data, machine learning had proved its worth even before the introduction of applications such as chatbots or mobile applications. With the changing consumer behavior, financial establishments now understand the necessity for improved risk management, customer satisfaction & engagement, investment prediction, cybersecurity, and many more limitless functions. Though many fintech processes work on predictive algorithms, but still there is a need to have a platform o system which serves more than predictions and seamlessly connect every entity involved in a financial process. In order to outwit business competitors and growth, leveraging technology is not a treat for companies but an essential part of the business. In this era of the digital ecosystem, the impact of machine learning in the financial sector is very crucial.

Machine learning had been a part of financial systems from the past but has appeared as a buzz very recently. It has now become an integral part of the life between the financial system and consumers as to how investments are done, banking functions are carried out and users getting insured. Machine learning is a technology that enhances the way services are provided by any connected system through statistical models created in a manner that it identifies data patterns and make predictions accordingly. Machine learning is reflected as an artificial intelligence technology that permits software applications to make informed decisions for better outcomes, without any external programming. This can be understood in a simple example. For any computer stored games such as chess, the system is already programmed for the winning steps. But in case of machine learning, algorithms are set such that it defines a set of rules for playing the right moves that can lead any player to win. In this, the system had to learn the moves by playing the game multiple times and reach a winning part. Similar kind of rules is defined for banking and financial systems, in order to detect fraudulent practices.

The scope of Machine Learning in Fintech Application Development-

With Machine Learning playing an integral part of finance and banking systems, right from managing risks, assets, approval of the loan and other investments; it has taken a major part of our financial lives. Whether it is personal finance or consumers experience, managing frauds or wealth management, the finance sector has explored every bit of machine learning. The basic characteristics of this technology that makes it worth utilizing are:

Speed:  Money trading, stocks or other financial transactions require speed, as a difference in the fraction of seconds may attribute to heavy loss. With machine learning algorithms, the past data is quickly analyzed and serves a great speed for transactions. 

Consistency & Reliability: For any financial establishments to perform better, it is important to build trust with consumers, with regards to security of personal identity & transactions. Systems integrated with machine learning functionality are trusted and free from fraud.

Security and Accuracy: Financial systems are prone to cyber theft and hacking. Machine learning is capable of identifying distrustful patterns and segmentation of data sets to predict fraud based on analytics. As Machine learning focuses on the analysis of past data and predicts based on same, it provides better accuracy for any financial trading operation.

Benefits of Machine Learning in Fintech Application Development-

Some of the key advantages of machine learning are enlisted here:

Improved Portfolio management: You must have come across the systems or portals that accept user details such as age, income, investments etc and based on these details provide you with information related to monetary benefits. For example, robo advisors which are not robots but algorithms that collect and analyze the user data and make suggestions across asset management for achieving user goals. This robo advisor is a machine learning algorithm (which is actually a virtual advisor) extensively used by financial institutions to combine user data and real-time market scenario and deliver better investment decisions for the individual user. The information shared by the virtual advisors are validated and in line with the present market conditions.

Fraud Prevention: With companies having all their data and user information online, the sight is more prone to fraud or security risk. The traditional risk assessment systems were based on complex set of rules defined to prevent risk, but the modern fraud detection capabilities comprise of machine learning technology that actively learns the risks based on previous assessments and define rules for the probable hacks and thefts. Based on user activities and previous transaction behavior, machine learning detects the flaws and flag them to alert for security. Given the higher volumes of cybersecurity thefts, machine learning systems are a must to have for financial and banking process.

Better Customer Service: One of the major concerns across all the industries is handling customer support and experience. The introduction of chatbots and other communication interfaces have changed the way consumer grievances are handled. Earlier, the consumers get frustrated with the automated phone support but with the machine learning, the system understands user requirement and furnish service and products based on previous account action. Machine learning provides an enhanced virtual consumer support system (virtual assistants) over an interactive interface.

Improved Risk Management: Machine learning works by analyzing the user’s financial status, balancing and checking them based on the real-time market scenario and making investment decisions accordingly. Analyzing data helps the user to understand the risks involved in maintaining assets and make recommendations to manage risks. Machine learning also predicts the burden on an individual account and assign investments managers to deal with particular accounts.

Improved Investment Predictions: As is the case with other functions, machine learning applications are of utmost importance to the trading market. The traders allot a pre-determined selling rate for a particular stock and as the market reaches the defined value, the automated system initiates the trading process. Machine learning is extensively used by fund managers to predict the market changes and set value of funds which was impossible with the traditional trading models. Many top financial institutes use machine learning based investment advisers to power the financial change.

Best Marketing Tool: Regarded as one of the best marketing tools, machine learning technology is used to analyze the web and mobile activity and previous campaign response from users to strategize new marketing efforts.

The Conclusion

Whether it is next generation personal finance management or capital markets and investments banking, from peer to peer lending and other payments processing, one-stop business shops to mid and small finance enterprises; machine learning capabilities are the new norms. Assisting with the sales recommendations and introduction of the new financial products, machine learning is clearly a must-have a solution for the financial sector to create a trustworthy and reliable ecosystem.

Note: Originally submitted on Linkedin -  FinTech Application Development: How Machine Learning is Making it Better.

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Fintech Trends in 2018