Salesforce says with the use of data science, predictive marketing accurately predicts which marketing strategies and actions are best likely to succeed.

That is “Predictive Intelligence which drives Marketing Decisions”

Predictive analytics according to SAS is “the use of statistical algorithms, data and machine learning techniques to identify the probability of future outcomes grounded on historical data”. Here motto is to provide a best possible assessment of what would happen in future by going beyond what has happened.

In this post I have tried to take you through some of the best marketing applications of predictive analytics.

Qualify and Rank Leads

Finding best match leads and prioritizing them is the basic work which if done correctly would further help sales and marketing teams to apply correct strategies. Insights generated from predictive analysis can help them to focus and nurture most profitable customers. Sales and marketing can move in a better position and would close down more easily. Small and large companies can earn a good return on investment from predictive analytics techniques involving sales data.

Predicting Customer Behavior More Precisely

For marketers, the most important thing is understanding customer – what they need, when they need and how is most important for generating business. Predictive analytics techniques guided by artificial intelligence and machine learning helps to predict future customer behavior by identifying similarities and differences customers’ past purchasing behavior to judge the probability of their future purchases. Predictive models can better guide you to anticipate customers’ behavior for better marketing strategy.

Bringing Correct Services/Products to the Market

The ever-expanding cognitive technologies of data visualization and predictive analytics are opening new doors of opportunity to companies attempting to solve complex issues. Data visualization is not just a tool which appeals to the eye but it is also used to guide, inform and inspire actions depending on customer behavior (and other business data). This helps to bring the right products and services to the customers.

Aiming the Right Customers with Right Content at Right Time

Predictive analytics is the simplest method to achieve quick response on better ROI optimizing a marketing offer. Predictive analytics users are up to twice more likely to judge high-value customers and market the correct offer as reported by Aberdeen Group. A range of predictive analytic models like response modelling, affinity analysis, churn analysis etc. are available for the same.

Using Predictive Analytics Insights to Drive Marketing Strategies

Some of the uses of predictive analytics in marketing include:

• Gain access to social media data
• Accessing internal structured data
• Relating behavior scoring to customer data

Predictive analytics insights can quickly help to determine whether a marketing campaign over social media would have a larger impact or whether a one through mobile is more apt for the target audience. Sentiment analysis and text analysis applied to social media data is one more example which can be used to help boost marketing campaigns and capture insights for future product creation.

Thus we can say data has become the new oil. With rapidly changing technological landscape, companies which will succeed would empower their employees to use tech-first solutions to serve their customers better.

Survey base reports claim that currently firms are spending estimated $36 billion on infrastructure and storage. This figure is expected to double by 2020. With more data, better computing capabilities and easy access to vendor tools, predictive analytics for marketing have jumped from smart to a business imperative.

Share your comments and feedback on this post.

Happy Exploring!!

It is very well said by Gerald Cohen “Business intelligence is not just about turning data into information, rather organizations need that data to impact how their business operates and responds to the changing marketplace”.

Business intelligence tools are an important way for a business to generate useful valuable insights, resolve urgent concerns, monitor data, and necessary components to make better and smarter decisions that drive positive results.

In this article, I would be discussing some of the top Business Intelligence tools for 2018, compare their abilities to analyze, categorize, capture data and extract the best practices for improved judgement.

1. Tableau

• One of the top-rated BI tools and intuitive business platform, the tableau is known for its single-click rapid reporting.
• Supports data visualization and data exploration.
• Supports mobile BI strategy and integrates with Microsoft SharePoint.
• With Tableau, you can create dashboards, publish and share it easily.

2. SiSense

• End-to-end proprietary BI tool built for those users who are not much used to BI.
• An agile BI solution, SiSense allows businesses to analyze disparate and big datasets helping to generate business trends.
• With advance tools, it supports, manages business data along with eye grabbing visuals, reporting and interactive analytics.
• At a very high speed can query big data.
• Ad-hoc Reports, Ad hoc Analysis and Ad hoc Queries are key features of SiSense.
• Can export data to CSV, PDF Images, Excel and other formats.
• Comes with both web-based and mobile deployment and bench-marking.

3. SAP Business Intelligence

• This BI tool with robust infrastructure is for those businesses which require a detailed view of all the company processes.
• Get wide ranging functionality in one integrated platform with SAP BI.
• Get full support for cloud deployment or on premise.
• With simple data warehouse design, the application built using SAP can incorporate with any system.

4. Microsoft Power BI

• Microsoft Power BI is a self-service business intelligence cloud service most popular for its seamless connectivity.
• MS BI allows any user to with tools to analyze, visualize and share data through Excel.
• Its dashboard helps track businesses, enables report-sharing and can be accessed from any device along with other collaborative features.
• With self-service capabilities, this tool delivers insights throughout the organization.

5. Yellowfin BI

• Comes with easy to use BI tools which can become universal throughout a company.
• Access your dashboards anywhere: company intranet, web page, wiki, or mobile device.
• Data-rich presentations and interactive reports making user’s insights more valuable.
• Yellowfin BI also supports the business decision-making process.

So this is my take on five best business intelligence tools. Each has its own pros and cons; you can select the best as per your needs.

Do share your feedback on this post and stay tuned for more important stuff on BI.

Happy Exploring!!

“The important thing is not to stop questioning. Curiosity has its own reason for existing” – Albert Einstein

(Image Source – iCloudHero Digitial Agency)

By now most among us are aware of Salesforce Einstein. In this post, I have tried to glance through how this amazing technology would benefit your business.

With advance technology, it has become a must to run your business on a platform which provides you with cutting edge technology of cloud, artificial intelligence etc. Salesforce Einstein the amalgamation of the name itself is innovative and revolutionary. Powered by artificial intelligence, Salesforce Einstein is a complete end-to-end B2B marketing solution. (AI is the science of building intelligent machines, particularly intelligent computer programs. AI is the next big thing which will transform our daily lives.)

Built on world’s best CRM platform, Einstein supports sales and marketing teams to target their accounts accurately, customize their campaigns and engage with their businesses. Salesforce Einstein unleashes the benefit of Salesforce’s predictive analytics, deep learning, natural language processing, machine learning (ML), and image processing to work as a robotic account manager.

Michael Kostow, SVP and GM, Salesforce Pardot quoted “Identifying the most valuable sales accounts to secure new business remains a challenge for many B2B companies. Often times, there are many decisions makers within a targeted account, and it’s hard to personalize engagement at scale”. “Einstein ABM redefines B2B marketing, finally giving sales and marketing professionals the tools they need to secure new business and growing existing accounts, all on one platform and powered by AI.”

With Einstein Account-Based Marketing (ABM), users have a data scientist working for them without any requirement of model management or data preparation. Let your CRM grow bigger, smarter, more productive and with happier customers.

Salesforce Einstein enables the business to:

• Synchronize Sales and Marketing: Einstein ABM insights support sales executives with all the latest news prospects like merger acquisition activity, financial results etc. to keep them updated with engagement strategies. They then further use Salesforce Engage to customize marketing content reaching out to prospective leads within the accounts. Executives can also utilize dashboards to check the effectiveness of the messages, click-through rates of the content and exact time when it is opened up.
• Identify the Correct Accounts: With Einstein lead scoring, one can automatically get to know which accounts are more likely to get converted based on certain factors like past purchases, relationship history etc. Advertising studio allows marketers to advertise and market to the new “lookalike” prospects by identification of audiences with the same profile, looking at the online behaviors from existing CRM database.
• Optimize, Measure and Modify Marketing Campaigns: Salesforce Einstein with a single dashboard can explain insights into which campaigns can perform best and why. This can help sales analytics and B2B marketing companies to understand and perform better with their marketing campaigns. Marketing companies can identify the required attributes of marketing campaigns which have the best potential to drive sales for required accounts with new Multi-Touch Campaign Insights. As for example, it can decide the sequence of downloading an eBook, clicking on an ad, and watching a webinar will it be a correct journey to convert prospects into best quality leads.
• Improves Engagement of the Account: With a leading solution in the form of Engagement Studio, sales and marketing executives can send customize emails as per qualifying values of the buyer or real-time buyer behavior. For example when a particular lead likes a particular piece of content or has a significant influence on its purchasing decision. Also one can determine overall lead engagement, competitor involvement and customer sentiment to know how the deals are progressing with Einstein Opportunity Insights.

Being the first comprehensive AI for CRM, Salesforce Einstein allows companies to be more predictive, smarter in knowing their customers. Without any prior extensive training, Salesforce Einstein works incredibly. So without worrying about anything, one can reap the benefit of amazing technology for their businesses.

This was just an overview of some of the salient features of the intelligent CRM, Salesforce Einstein. You can dig deeper to learn more about this product.

Share your feedback and comments on how Salesforce Einstein has helped your organization.

Stay Connected for more helpful stuff.

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May 25th, 2018 is fast approaching, the day when General Data Protection Regulation would go into effect. This would impact how companies manage personal data.

In this write-up, we would mainly glance at some of the important points which you need to know about GDPR Compliance.

We are a part of the digital world where accessing our personal information has become quite a ubiquitous part of our day to day life. This has left us with the increasingly lesser idea to know who is accessing our data, from where they are accessing and for what they are using it. With much talked high profile data breaches during the past time, it has now become mandatory for citizens that their personal data should be protected.

General Data Protection Regulation has now become “Now or Never” situation for businesses. GDPR is aimed to replace the existing Data Protection Directive (Directive 95/46/EC, or DPD) with a new set of the framework which would increase responsibilities of organizations. Complying with GDPR would ensure the protection of the personal data and privacy of European (EU) citizens for all the transactions that occur within European member states. Non-compliance would cause hefty fines of up to €20,000,000 or 4% of worldwide annual revenue (whichever is higher) based on the specific violation.

Elizabeth Denham – UK Information Commissioner in her lecture on “GDPR and accountability” for the Institute of Chartered Accountants in England and Wales quoted “We’re all going to have to change how we think about data protection.”

For both large and small companies GDPR compliance would not be easy, it is a complex and huge undertaking. However, we all will have to move with the regulation and it is imperative to know the same from the core.

Some of the important rights highlighted in General Data Protection Regulation for individuals with respect to their information are:

• The right to be informed;
• The right to be forgotten
• The right of access;
• The right to rectification;
• The right to object;
• The right to restrict processing;
• The right to data portability;
• The right not to be subject to automated decision-making (such as profiling); and
• The right to an explanation if an algorithmic decision was made about them

Further information can be accessed via ICO’s Overview of the General Data Protection Regulation.

Now let’s look at the types of privacy data which would be protected by GDPR:-

• Basic identity information such as ID numbers, name and address
• Biometric Data
• Genetic Data
• Health Data
• Sexual Orientation
• Racial Data
• Web data such as location, cookie data, IP address and RFID tags
• Political Opinions

To Whom Does GDPR Apply?

GDPR applies to both ‘Controllers’ and ‘Processors’ of the data. A processor is a party who actually processes the data while data controller states how and why personal data would be processed. So the data controller can be any company or organization or government. While data processor can be any IT firm performing the actual data processing. It would be controller’s responsibility for ensuring that their processor abides by data protection law while processors would abide the law to maintain their activities. Under GDPR, if processors are involved in a data breach they would be would be far more responsible than were under the Data Protection Act.

GDPR would still be applied even if the processors and controllers are based outside the EU, as they would be dealing with data belonging to EU residents.

Although the above information is just a glance through GDPR, achieving complete compliance would help you enable to establish a clear view of your data, where it is placed, how and which company processes it and how to quickly access the same to make key changes. Digital tools would help a lot to get full visibility of your organization’s data structure and saving time.

Let’s ensure that we fully comply with GDPR.

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“Sales is an outcome, not a goal. It’s a function of doing numerous things right, starting from the moment you target a potential prospect until you finalize the deal.” – Jill Konrath

The way consumers interact with brands is constantly changing with the progression of media. To gain potential benefits, marketers must re-visit their organizational structure, ways of working and their present strategies.

The core elements for great sales insight exists in every company. It is very well known that a company’s ability to drive market growth depends on consumer insights and how well it transforms those insights into operative action.

This post helps to glance around sales and marketing insights which are tremendously powerful when they are used correctly and are well-crafted.

Begin with the ‘Typical’ Customer Problem Scenario

Business is all about satisfying your customers’ needs. All the customers have different problems, but a few of them have truly unique problems. Those problems are that which are just not understood at a detail level in that particular customer’s context.

Companies catering in the same region and similar market, their abilities to meet those challenges differ while the context remains similar. This is how business functions. Application of quantitative and qualitative marketing research techniques, approaches and tools help clients to uncover why their customers behave as they do at every phase of their purchase journey, dig deeply and understand their customers’ experiences.

Remember your product was built firstly to help fix customers’ demand or filling the gap in the market.

Always Take into Account Buying Personas

Keep in mind, companies don’t buy rather people do. There will be multiple personas in a typical B2B scenario, intricate with the buying decision. Each scenario has different issue and concern which they care for. If, for example, you are selling a Tableau Software, the VP Sales in the buyer’s organization may care about how the software will help with sales productivity, while the CIO is more likely to be concerned about the data security concerns and deployment effort. Thus Insights must be designed keeping in mind the buying persona of people.

Bring Something New to the Customer’s Table and Make it Interesting

While addressing the buyer’s needs, always make sure to demonstrate your understanding of how a customer might use your solution to meet those needs. Make it fascinating for the buyer so that the buyer says “that’s interesting, I never thought this way before”. Buyer should feel that you both would be benefited from that approach.

Create an Insight that Leads to the Solution

If you possess a deep understanding of the subject “as to why the product was developed in the first place”, you can easily create an insight which lands to your solution. Use your insight which leads to your product’s fine capabilities mapped with customer’s unknown or known requirements. Always do not prefer using traditional marketing approaches to lead with the product.

Avoid Self-Promotion

Self-promotion which is presented as an insight always does more harm than good. Insights you provide should have some core value, whether or not customer goes with your product. Each of your resource should force the buyer to think in a different manner about the opportunities or challenges in front of them. Focus on using the insight to build credibility.

Lastly, smart technology would help you to connect your solutions to the customers’ business problem and deliver correct insights at the correct time to the correct persona.

So this is it from my end……Do share your views on the post.

Happy Reading!!

Welcome to the world of fastest evolving business intelligence (BI) and data visualization tool.

An inevitable aspect of business analytics is data visualization. With more and more data sources being discovered, there is an increasing need for data visualization software’s which can help business managers to visually analyze trends and decide on quickly. At present, Tableau and Qlikview are the most widespread tools for data discovery/data visualization.

IN THIS POST, I WOULD BE PUTTING MORE LIGHT ON TABLEAU PREP.

Today data preparation takes maximum time and is one of the biggest challenges faced by many of us. A recent survey by Harvard Business Review claims that people spend 80% of their time shaping and cleaning data while only 20% of their time is spent in data analysis. Converting data to a useful form is time consuming, hectic and requires specialized skills.

A brand new data preparation product from Tableau, Tableau Prep is designed to empower people to confidently and quickly clean, shape and combine data. Also, the time from data to insight is reduced tremendously with smart features to simplify and automate difficult tasks, integrating Tableau analytical workflow for quicker speed to insight.

This software comes with customized visual experiences making complex but common tasks like unions, joins, aggregations and joins simpler. No scripting is needed, just drag and drop. You can see your data transforming right before your eyes with Tableau Prep. With intuitive dashboards, you can reap your desired results quicker and with much more confidence.

“Before Tableau Prep our team would spend hours and hours making sure that our data sources were clean and organized, just to make sure that our analysis was accurate and effective,” said Gessica Briggs-Sullivan, Tableau Administrator at Charles Schwab, Inc. “We’ve been able to save hours of work with Tableau Prep, completely reinventing the way we look at our data, and dramatically shortening the time between data collection and actionable insights.”

Get an Entire Picture of Your Data

3 coordinated view helping you to see a complete picture of data profiles of each column, row-level data and data preparation process. You can select whichever view as per your task requirements.

Tableau Prep is Smarter Making Your Work Faster

With fuzzy clustering, make your repetitive tasks into one click operations for example grouping by pronunciation. Work with smarter features to fix common challenges with data prep.

Quicker Results

With each of your command, you can instantly view your data change, even with millions of rows and columns of data. Get the freedom to experiment without consequence, re-order your steps, directly edit a value, you select. See the result instantly as you change your join type.

Maintain the Flow of Your Data

Bridge the gap between analytics and data preparation and get better business outcomes. With Tableau Desktop it is easy to open your output or share it via Tableau Online or Tableau Server with others. An easy method of sharing helps reducing friction and allows you to stay in the flow of your data analysis.

Get the Freedom to Associate with More Data

May it be data from a spreadsheet or in the cloud or on premises, with Tableau you can connect to all. Without writing code, you can clean up disparate data, access and clean your data. The software allows you to intelligently take advantage of your existing database investments by pushing operations down to the database as and when possible enhancing execution performance.

Collaborate and Share Securely

Tableau Online or Tableau Server allows you to create an environment wherein all in the organization can work with the governed data by sharing it securely.

Tableau Prep also controls Tableau Desktop calculation language, data connectors, certifications and permissions so that you can get up to the mark within no time and collaborate at any junction in the analytical process.

A part of Tableau’s new tailored subscription offerings includes Tableau Prep with the new Creator offering. If you are an existing customer of Tableau Desktop then at no cost you can use Tableau Prep for next two years.

For further information on Tableau Prep please visit www.tableau.com/new-features.

Click on the link and get 14 days free trial https://www.tableau.com/products/trial

Share your feedback after you use Tableau Prep. For more such posts, stay connected.

HAPPY READING!!

We are surrounded by artificial intelligence (AI) and we may not even know it. The tasks which were once reserved for humans are now been taken over by machines. In this blog, we would glance as for how artificial intelligence would soon be that prominent transformative technology which would change human lives.

One of Britain’s pre-eminent scientists, Professor Stephen Hawking quoted to BBC – “The development of full artificial intelligence could spell the end of the human race.” He said that the primitive forms of artificial intelligence developed till date has proved a boon but he fears the consequences of making something that can surpass or match human-beings.

Artificial intelligence revolution has unimaginable potential, to transform wide-ranging areas which were unimaginable earlier. In coming years AI would revolutionize every aspect of our life, including medicine. Tech giants like Google, IBM are strongly working towards patient data mining which proves that there is something in this field worth giving time. FDA Commissioner Scott Gottlieb during the Health Datapalooza conference in Washington, D.C. said: “AI holds enormous promise for the future of medicine”.

Healthcare sector would soon be taken over by artificial intelligence, for its betterment. This advanced technology would help medical professionals to research best design and methods to treat every patient. AI would improve the patient experience at large. The recent advisory report quoted, “Artificial intelligence works best when paired with humans.” The main objective is to use AI for creating competencies across the gamut which would not only support staff in their respective roles but would also free caregivers, clinicians and other staff so that they can focus more on much required value-added activities.

According to one of the analyses conducted by Accenture, by 2021 the growth in the AI health market is expected to reach $6.6 billion—that’s a compound annual growth rate of 40 percent. In just coming five years the health AI market will grow more than 10×2.

Some of the below point to explain how this technology (AI) is used in the healthcare sector:

Workforce – Amidst increasing labor shortage in healthcare, artificial intelligence offers a great way to fill the gaps. AI has the power to relieve the burden on clinicians and provide workers tools to perform their jobs better.

Supports Insurance Verification – Insurance coverage information, for the doctor’s office, is digitally verified so as to reduce manual calls required to ensure that all the required patient’s information is perfect and valid.

AI Chat Bots – AI chat bots can easily take up the role of an office assistant by automating many required tasks. With faster search operations, it can support recommendations 20% faster than performing a manual search.

Optimize Supply Chain – Employee queries can be quickly replied to by AI with many days on spare. Also, AI can track unused material supplies to minimize excess inventory. This can save a lot of time for the clinical staff and automate future delivery and order.

Automating Financial Process – Artificial intelligence can enhance the payment process, helps in creating invoice and vendor patterns, detects payment and automation of payment for an approved invoice and save a lot of time.

Supports and Expanding Self-Service – Healthcare employees who don’t have access to computer systems like lab technicians, for them AI is an accurate and quick way to empower cross-functional self-service.

Boosting Cybersecurity – Immense data workflow of IT professionals can be solved by AI and machine learning. Thus critical patient information can be safeguarded.

Optimizing a Restful Environment – Key to patient satisfaction and better outcomes is a perfect healing hospital experience for a patient. When AI is preferred to maintain and manage hospital equipment can help the staff with much needed medical insights. It can also schedule regular maintenance, fixing issues before they erupt. It can also eradicate the common source of noise before they become big chronic problems.

Reach Care – By integrating health data across platforms, Artificial intelligence can magnify care reach. Various data sources are required to be connected to the smooth patient experience.

The above mentioned points are the major contributors to not only the patient to heal, recover and get the restful sleep but also boosting their satisfaction score which can affect hospital’s reimbursement levels.

Healthcare sector has just started to unlock the potential of AI; there are many possibilities to benefit in the near future. As of now, impressive results are being gained by staff and other supporting caregivers to help them work in smarter and better manner.

Hope you enjoyed the post; share your comments and feedback.

Stay connected for more.

Late British economist and author Ronald Harry Coase quoted “If you torture the data long enough, it will confess to anything”.

Today lack of data is not a problem rather taking a correct decision with too much data is a problem. Performing data analysis correctly has become a must so that it becomes easier to manage such an overwhelming volume of data correctly with a clear decision.

Acquiring data analytics skills in not an overnight job, but it’s an ongoing process. Identifying your mistakes and gradually changing your approach can lead you to more appropriate and sound practices.

In this blog, I have attempted to identify some of the most common mistakes which should be taken care off to improve your data analysis skills.

Always keep in mind that data analysis may not provide the necessary risk assessment that your business requires if any of the five factors that are consistency, completeness, accuracy, relevance and timeliness are absent.

Correctly Define Your Questions

Data analysis requires correct questions to be asked. Always check whether your questions are clear, concise and measurable. Questions designed should either qualify or disqualify potential answers to the specific problem.

Set Appropriate Measurement Priorities

It is necessary to understand what should be measured and how to measure it. Always check what kind of data is required to answer your questions. Data should suffice your questions and should not be vague. Also, make sure that you include reasonable objections which can hinder your answers and then move on.

Measuring your data is also equally important, and it should be done before collection of data is completed. Measuring data either supports or questions your analysis in later stages.

• Always set your time frame,
• Know your measurement unit
• Decide factors to be included while measuring the data.

Data Collection

Before starting a collection of new data, analyze well that what all information you can get from existing data sources and collect them first.

As you begin collection of data now, make sure to organize the same properly and take a note of all important points. Prepare a log of all the collected data with a time stamp.

Keep ready a file for naming and storing the data, this should be centrally placed for all team members to work. This would prevent duplicity of data and save time.

Do Not Focus On Limited Variables or On All Variables

Studying only one variable or example can make your conclusions go wrong or off the mark. Judging everything based on 1 or 2 key metrics, will not give you a complete picture of the situation. Also focusing on each and every variable or metrics collected would be a bad idea. Hence for appropriate data analysis, it is essential to have a perfect view of your requirements.

Don’t Fall Prey to Confirmation Bias

This is when data scientists prefer to use limited data to prove a hypothesis which they feel is correct and ignore other data sets which fail to align their hypothesis. Make sure that every time you prioritize your objective and challenge your assumptions

Analyze Data

Once you have reached this step, it’s time for deeper data analysis. Avoid the consequences of statistical data analysis, when you manipulate data. Analyzing trends, variations, correlations and outliers would help you to focus more on your data analysis and thereby answering all your questions and objections.

Different software and data analysis tools are of great help at this point. Always stay up-to-date with recent data analysis news in your field, latest trends and new learnings in the day to day life of data science.

Data Interpretation

As you begin interpreting results achieved, always look for the following answers

• Does the data, justify your original question? If yes how?
• Does it allow (data) defending any objections?
• Are there any limitations to your conclusions or any aspects which you have not considered?

If your interpretation successfully answers all the above questions, it means you would come to a productive inference. You can now use the results of the data analysis and move on with the best course of action.

Although by reading the above post you cannot become a better data analyst in a fraction of a second. But improving and polishing your data analysis skills with time and making changes to your approach can lead to more sound practices.

Well, the taste of the pudding is in eating — Happy Reading!!

“INFORMATION IS THE OIL OF THE 21^ST CENTURY, AND ANALYTICS IS THE COMBUSTION ENGINE”…PETER SONDERGAARD

We are well aware that sales and marketing can be a guessing game. Strategies are planned in a business with great risk as to whether it would succeed or not. If the sales figure increases, it is assumed that the strategies are successful and they are continued. If there is no improvement, more efforts are made till maximum deals are closed.

Today technology has given us the power to monitor the output of our strategies. Gone are the days when one had to research hard to find breathless paragraphs on the power of analytics. In the present era, sales world we can get numerous examples where data analytics is delivering significant improvements in effectiveness, growth, and efficiency. Data analytics can be helpful to monitor customer activities and connect them to specific sales efforts. Now let’s have a glance through some of the ways businesses are using analytics to improve sales.

“IN A SURVEY CONDUCTED BY MCKINSEY OF MORE THAN 1,000 SALES ORGANIZATIONS AROUND THE WORLD, IT WAS FOUND THAT 53 PERCENT OF THOSE THAT ARE “HIGH PERFORMING” RATE THEMSELVES AS EFFECTIVE USERS OF ANALYTICS”.

Track Your Sales Leads

In sales, leads are the foundation of the actions to be taken by the sales team. Data analytics helps in improving the accuracy of the leads generated. Apart from the traditional approaches, companies now prefer greater predictive insights combined with intelligent automation to identify the most promising prospects and identify the most appropriate time to target them. You can thus unlock powerful perceptions into which sources of sales leads are truly motivating your business growth.

Predict Behaviors

Data analytics can help in predicting the most suitable leads which can save a lot of time wasted calling the leads that are less likely to be interested. If suppose your business has always sold a certain type of product A, with predictive analytics you can look at past customer interactions and predict where future sales will go with that product A. Analytics can also help to predict and compare the outcomes of different marketing and promotional campaigns.

Email Campaigns

Email is a great way to reach out to a larger chunk of prospects at once. Although most of them won’t purchase based on that email, at-least a few may call asking for further information. Data analytics can help you to determine which subject lines of the emails got the most response and which types of messages are more likely to generate phone calls that lead to success. Analytics can also help in deciding the best time and day to send emails to your list of probable customers.

Business competition is keeping companies on their toes. Data Analytics hence can help a business with its marketing and sales efforts saving a lot of time, effort and money which is wasted on ineffective tasks. It is a powerful tool for sales teams so that they can make the most of their efforts and close more prospects.

Share your feedback and comments on how Data Analytics has helped your organization. Stay Connected for more helpful stuff.

Happy Reading!!