Three Essentials For a Good Omni-Channel Retail Process
Only 5% of US retailers in a 2014 survey said they had executed on most of their omnichannel strategy. Lack of cross channel integration troubled end customers with issues like different retail pricing and cumbersome return process. According to a research firm – RIS, “$45 Million are lost in sales for every billion dollars in revenue, because of lack of cross-channel integration”. Today, customers and their demands have evolved seeking a seamless shopping experience, irrespective of their geographical location. To cater to this market and enrich the user experience, the big brands are shifting from segment oriented focus to individual-oriented focus. With product and price comparisons across all marketing channels, retailers are bound to stay consistent on all product information and prices. The order-management system needs to support these changes in business processes. It should identify the channel through which the order was processed and analyze the discounts/price changes to be applied. Competition is driving retailers to improve user experience. According to RIS, “6.5% is the amount of revenue lost because of the lack of omnichannel readiness.” In order to make the omnichannel commerce a success, we should have: An efficient Order Management System – using which the retailers can process their orders using dynamic fulfillment routing and inventory allocation system. The system will be well-versed to handle different order scenarios that may arise in addition to multiple return and cancellation options. It should also present a proper view of the inventory that is divided into multiple places, based on which the retailers can take decisions regarding its sales and fulfillment. Without the fulfillment system in place, an order cannot be called a completed order – so, the system should also facilitate the store fulfillment which will help the retailers to sell the products to customers where even the carriers refuse to cater. Customer Knowledge – today, the retailers should go the extra mile to know their customers, their preferences, purchasing behavior and product feedback. They should be open for a flexible process wherein they would incorporate essential feedbacks and optimize their end products/services. A Modern Platform – the retailers need a modern platform with cloud and mobile services that can provide analytics based on tracked customer preferences. The current day market also requires a proper presentation of centralized product data and other customer-facing technologies like self-checkout, kiosks, mobile payments, e-Coupons, etc. and easy integration of systems.
No More SFDC Training at the Bottom of My Bucket List
Are you having a really slow start on your SFDC management or development training? Up until summer 2014, if you wanted SFDC training, you could officially take a class, buy a 3rd party book, or use the online SFDC help and training articles. (BTW, there are other un-official free resources, such as sfdc99.com). Honestly, I don’t personally know anyone who enjoys using the standard ‘Help & Training’ to learn about SFDC. However, lucky high rollers on Unlimited or Performance editions get exclusive access to additional interactive Help & Training content. Having been aboard one such high rolling ‘whale’, I can testify that interactive training makes a ton of difference. If you’re on any such organization and didn’t know, you’ve been missing out big time! Classroom training suits me best. I’ve been a trainer. There’s just no substitute when you’re easily distracted – but then again, not all trainers make their classes fun. Reading books will do the trick as well, but it’s definitely not as fun as attending a good class. I haven’t heard of any must-have SFDC books though. Enter Trailhead. SFDC’s challenging and innovative approach to Web2.0 training. Yep, that means real social & interactive training. [I promise to add ‘fun’ as soon as they add -tangible- perks to it]. Trailhead is still in the beta stage, and hosts 7 training trails as of August 2015, up 4 since June 2015: Beginner admin – about 9 hours’ worth of content and 10,200 points earning potential CRM admin, about 1.5 hours’ worth of content, and 2,200 points of earning potential Beginner developer, about 15 hours’ <minimum> and up to 19400 points worth Intermediate admin, about 6.75 hours’ long, with up to 8500 points to earn Intermediate developer, about 10.75 hours’ worth of content, and 8400 points to earn Mobile SDK Developer, near 7 hours’ long, and 3000 points of earning potential Dreamforce ‘15, only 30 mins and 300 points -Late August Update- There are now 11 trails, after the addition of: Admin Lightning Experience – 3.5 hrs, 1100 points Developer Lightning Experience – 10.5 hrs, 5800 points Admin Trail, starting with the Lightning Experience – 3 hrs, 1000 points Sales Rep Lightning Experience, 2 hrs, 600 points I’m figuring the ‘Lightning Experience’ will be well received by SFDC at Dreamforce ‘15 You may select to just chopper in and drop into the middle of any trail or challenge. You are not forced to follow the recommended sequence. You are required to use a developer org and an admin login to complete some of the goals. Each trail consists of a number of topics, each within an independent page. Within each topic, you are challenged to complete a short test or a developer org configuration task. Your success will be rewarded with X points. If you fail; “no soup for you!” (Google up ‘Soup Nazi’ for that reference). Retries will earn you half the points of the previous attempt’s reward level. Interestingly, the trailhead is capable of checking whether the configuration (metadata) you were challenged to complete exists within your developer org. In addition to points, you are rewarded with ‘virtual badges’ for completing challenges and reaching point thresholds. There are links for related articles within each topic and links to SFDC forum discussions. If any such article or discussion picks your interest, you may take the long way for your trail. So what do you do with those badges and points? Back in January, you’d get a free t-shirt for completing the existing trails. These days, points and badges will only get you bragging rights (what? I can’t write that?) – a-hem! I mean ‘community recognition’. So what are you waiting for? Do you want any additional motivation to start your free trailhead journey? Register for the SFDC IDEAS Community, and vote up “SWAG for Trailhead Points”! https://success.salesforce.com/ideaView?id=08730000000wkRxAAI
Why Do We Need SFDC Security Assessment?
Cloud application security specialists have warned salesforce.com (SFDC) users of the vulnerabilities in the application. Cybercriminals exploit such vulnerabilities to harvest user credentials. Phishing attacks trick users into clicking a link which would appear to be leading to salesforce.com. It is difficult even for the spam filters and anti-phishing solutions to identify such links, let alone the user. In 2007, an incident detected by an Atlanta based financial institution, revealed how a simple click on an email link compromised their entire SFDC organization. The action released a Trojan, resulting in the retrieval of SFDC passwords. Passwords retrieved by the cybercriminals were used to access information from thousands of undisclosed ADP and SFDC customers. In 2014, Salesforce.com alerted its customers about the DYRE malware*, which usually targets customers of large financial institutions. Cybercriminals came up with a version that threatens salesforce.com users. DYRE phish attacks usually consist of emails containing what looks like a genuine message from SFDC, with links or attachments as shown below. Such emails often employ scare tactics to get the users to download linked malware and/or execute the attachments. Dyre sample emails Source: spamstopshere & trendmicro Links usually point to a Trojan attachment or URL, which if executed, will initiate a ‘Man-in-the-Middle’ attack, quietly gathering credentials and user data. Some versions disable Windows firewall registry entries. Salesforce reacted by increasing mandatory security levels to all customer organizations, such as removing the capability of trusting any IP’s in your organization with a single IP Range entry. IT admins seeking to trust any IP to their SFDC org, are forced to take responsibility for lowering SFDC org security by creating a minimum of 254 range entries. The admins are advised to trust incoming connections only from VPNs and corporate static IPs. This measure is not enough to protect you. DYRE might enable a surreptitious download and installation of additional malware, such as VNC/remote management into the infected system, circumventing IP trust settings. Analysis of the newest versions of DYRE and similar cyber-attacks (UPATRE, ZBOT, CRILOCK, and ROVNIX) reveals designs to defeat email blacklists and the best filtering products. Even the best known products may detect and block just 65% of these phishing attempts. SFDC recommends the following initial steps to minimize phishing risk: •Train your users to spot phish or spoofed emails •Force shorter password expiration periods •Enable SMS-text identity confirmation to allow SFDC logins from unknown locations •Enable mobile 2-step identity verification •Enable SAML authentication and require all authentication attempts to be sourced from your network, or your VPN •Perform 3rd party security assessments and audits by trustworthy companies who are experienced in the field. (Preferably SFDC partners for your SFDC concerns) It is crucial to detect such attacks and protect users, as the stolen credentials can be used to extract sensitive data which can go undetected for a long period of time. * In June 2015, Trend Micro alerted of a 125% increase in DYRE-type attacks from Q4 2014 to Q1 2015.
What You See is What You Get
In the blog “Ad Impression and Click Counting: Are You Billing Your Customer Correctly?” I explained how ad impressions are counted and confirmed. The blog summarized scenarios, where customer billing may be inaccurate even when there are confirmed impressions. The steps behind this erroneous process are as follows: Ads are confirmed through a “client-side pixel” at specific position in an AD response. This is usually a transparent 1×1 pixel GIF. The URL for this image contains a unique identifier to record information that all the ads as per the request have been confirmed. For example, when a page is loaded, and an image is requested, all positions that were filled on the page are marked as confirmed. Thus, with this approach, billing will occur, irrespective of whether ads have been viewed by a user or not. What you see is what you get There is also a better approach which confirms only those ads which are seen by the user. If an ad is served below the scroll bar and the user leaves the page without scrolling, then the ad will not be confirmed. This approach has confirmation-URLs with every ad served and hence ensures that only those ads which are seen by the user are confirmed. The technical steps given below show how the confirmation-URL is different for each ad served. “Ads”: { “HPMiddle”: { “CampaignId”: 2827, “CreativeId”: 1, “Confirmation-url”: “http://www.adserver.com/d824f82Q2FQ5CQ5CQ5CQ5CQ5CQ5C5Q5C5hTq5qQ7ETQ3FQ5C…“, “Creative”: “content which will be served” “Classification”: “BigAd” “TopAd”: {“campaignId”: 2387, “CreativeId”: 0, “Confirmation-url”: “http://www.adserver.com/d824a21Q2F——R-RrPSRSQ24Po——–RQ24–RS)Po—-PRN-oQ24)”, “creative”: “content which will be served” “classification”: “Leaderboard” } }, Backend Logic for Conformation: When an ad request is made ,ad log file is created/updated with user information like Time;IP;County; Zip code ;Ad name , position, page along with unique 16 digit number mentioned in red below. Sample ad log entry 1409655663^CUNK^C170.149.164.65^Chttps://www.tavant.com^Cnyt2014_textlink_digisub_account_37Y93,,MA3^Cwin7^Cfirefox3^Cna^ CNY^C10018^CUS^CX^C0-9^C0^CUNK^C007f01012dd95405a35a0008^C00^C00^C0000005056ab6ce1^C0^C To summarize, the technical process is as follows: With each ad request, confirmation-URL is called which writes another log file. At the end of an hour, ad log and confirmed log file are processed, and a 16 digit unique number is generated to count the number of impressions of a particular ad. Hourly data is then accumulated to tally the number of impressions per day. This data is inserted into a database through nightly job scripts, to be used for reporting by other applications.
Handling image uploads with AngularJS
When developing web applications, one of the common use cases would be to manage image uploads along with validations for supported formats and sizes. Here, we outline a way to achieve this in AngularJS using a file reader service. File reader module This module is intended for common usage across all screens where there is requirement to read the file. You can include the following code in a file upload.js (function (module) { var fileReader = function ($q, $log) { var onLoad = function(reader, deferred, scope) { return function () { scope.$apply(function () { deferred.resolve(reader.result); }); }; }; var onError = function (reader, deferred, scope) { return function () { scope.$apply(function () { deferred.reject(reader.result); }); }; }; var onProgress = function(reader, scope) { return function (event) { scope.$broadcast(“fileProgress”, { total: event.total, loaded: event.loaded }); }; }; var getReader = function(deferred, scope) { var reader = new FileReader(); reader.onload = onLoad(reader, deferred, scope); reader.onerror = onError(reader, deferred, scope); reader.onprogress = onProgress(reader, scope); return reader; }; var readAsDataURL = function (file, scope) { var deferred = $q.defer(); var reader = getReader(deferred, scope); reader.readAsDataURL(file); return deferred.promise; }; return { readAsDataUrl: readAsDataURL }; }; module.factory(“fileReader”, [“$q”, “$log”, fileReader]); }(angular.module(“App”))); Update the value ‘App’ with the name of your app in the last line of the above code. Image reading and Validation Define a directive called ‘ngFileSelect’ to validate the image for supported formats, size and dimension. App.directive(“ngFileSelect”,function(){ return { link: function($scope,el){ el.on(‘click’,function(){ this.value = ”; }); el.bind(“change”, function(e){ $scope.file = (e.srcElement || e.target).files[0]; var allowed = [“jpeg”, “png”, “gif”, “jpg”]; var found = false; var img; img = new Image(); allowed.forEach(function(extension) { if ($scope.file.type.match(‘image/’+extension)) { found = true; } }); if(!found){ alert(‘file type should be .jpeg, .png, .jpg, .gif’); return; } img.onload = function() { var dimension = $scope.selectedImageOption.split(” “); if(dimension[0] == this.width && dimension[2] == this.height){ allowed.forEach(function(extension) { if ($scope.file.type.match(‘image/’+extension)) { found = true; } }); if(found){ if($scope.file.size <= 1048576){ $scope.getFile(); }else{ alert(‘file size should not be grater then 1 mb.’); } }else{ alert(‘file type should be .jpeg, .png, .jpg, .gif’); } }else{ alert(‘selected image dimension is not equal to size drop down.’); } }; img.src = _URL.createObjectURL($scope.file); }); } }; }); If the image is valid, the directive calls ‘getFile’ function to get the base64 url of the image for preview, as defined below. $scope.getFile = function () { var dimension = $scope.selectedImageOption.split(” “); fileReader.readAsDataUrl($scope.file, $scope) .then(function(result) { $scope.imagePreview = true; $scope.upladButtonDivErrorFlag = false; $(‘#uploadButtonDiv’).css(‘border-color’,’#999′); $scope.imageSrc = result; var data = { “height”: dimension[2], “weight”: dimension[0], “imageBean”: { “imgData”: result, “imgName”: $scope.file.name } } $scope.imagePreviewDataObject = data; }); } Finally, you can bind the directive to your input button, in html, as follows: <span class=”btn btn-default btn-file” ng-class=’class1′> Upload Image <input type=”file” ng-file-select=”onFileSelect($files)” accept=”.jpg,.png,.gif,.jpeg”> </span> PS: File reader module works correctly in all modern browsers. For IE, it was found to support version 11 onwards.
Remanufacturing – Reasons that Make a Rebirth for Old Parts Valuable to Businesses
“Remanufacturing is a standardized industrial process by which a previously sold, worn or non-functional product is returned to the equivalent, or better, condition and function of the new original product. The remanufacturing process incorporates technical specifications and yields a fully warranted product.”– ISO. The remanufactured automotive parts industry is estimated to be an approximate $85-100 billion industry worldwide, as per the reports from the Office of Transportation and Machinery, U.S. Department of Commerce (2011). Let us analyze the reasons that make remanufacturing valuable to businesses. Low-priced: Automotive Parts Rebuilders Association (APRA) suggests that about 88% of the original parts are reused in remanufactured machines. Remanufactured products are priced 20-40% lower than equivalent new products and come with an equivalent version of warranty terms. New product warranties cost 1-4% of its sales revenues, and if you do the math, an equivalent remanufactured warranty cost is lesser for the OEMs. The remanufacturing process usually begins with the OEM’s exchange policy to push new product sales and product returns from warranty programs. Lack of new parts, retention of old technology or up-gradation of technology into old parts and environmental consciousness are other incidents that trigger remanufacturing. As Good As New: A remanufactured part goes through the same level of processing and testing as a new product and often turns out to be better than the original. Remanufacturing a part created ten years ago will always give us the advantages of the technology & engineering improvements, giving us apart with improved specifications. While new parts like transmission come with a year’s warranty, a remanufactured equivalent comes with a 3-year warranty. The remanufacturing process comprises of rigorous testing and sorting where broken/worn parts that do not match industry standards is discarded. The selected parts are cleansed/inspected and fabricated where new components are installed and reassembled. The final product undergoes an even more strenuous testing process including visual inspection and mechanical tests such as decay testing, gauging and crack detection. Collecting, inspecting, disassembling and replacement/reprocessing worn-out parts are some basic steps to be followed as per ISO standards (ISO/TS/P 239 is the quality standard followed for remanufacturing). This process is backed with robust documentation and appropriate warranty issuance. Such an established process ensures a certain level of quality. Compensates for new part demand: OEMs tend to stock spare parts that are fast-moving. These fast-moving parts are manufactured after a lot of planning –planning involves identifying market demand, accounting for buffer stock and plan for setups at the shop floor to manufacture parts in huge quantities. Slow-moving parts fit into fewer machines and are not produced in small quantities as the costs associated are higher. This demand gap is met by remanufactured parts. Meeting the demand on time translates into reduced machine time and improved customer satisfaction for the OEMs. Sustainable Manufacturing Methods: In remanufacturing, the parts are closely inspected for reuse and undergo multiple steps of cleaning, segregation and reprocessing before it is fitted into the main machine. This way, the chances of parts directly reaching landfills are reduced. Since remanufacturing encourages reuse and reprocess of existing parts, this saves the energy and water consumption required to produce new parts. It also reduces the impact of emissions and effluents as a by-product of manufacturing. Remanufacturing extends the life of existing parts and ensures that sustainable manufacturing methods are followed. Benefitting from an economical, qualitative and sustainability perspective, Remanufacturing is making new inroads in the industry and is here to stay.
The Internet of Things and the Way it Impacts Life
Internet of Things (IoT) is a network of objects (electronic devices) with the ability to interact with each other without any human intervention, deployed usually in islands of disparate systems. What does this mean? We have a lot of smart home devices like lightbulbs, thermostats, TVs and motion detectors. The communication between these devices without manual help is what we term as ‘Internet of Things’ or IoT. For example, if the motion detector detects an activity, while there are no signs of the family members’ presence (watches, mobiles, etc.), then it triggers an alarm. Another example of automation/no human interaction event would be when the leak detector finds an over-threshold instance and communicates the same. Few Benefits: Remotely monitor and manage your devices (smart devices) Create rules that will automate your home, industry, etc. which will in turn help in saving energy bills and reducing manual labor Collect raw data for analytics and the raw data collected via various sensors help: a.Predict usual/unusual events b.Find any rules in the events c.Pattern recognition But where and how can the IoT profit users today? Industry: Predict equipment malfunctions and schedule service maintenance Monitor thresholds and send notifications (with the help of sensors installed in equipment) Process payments – based on user location, activity and duration for- public transport, gyms, theme parks, etc. Home: Control lights based on motion detection sensors and save energy Predict unusual events like door unlocking when you are away Avoid disasters using sensors that can track leakage/disruptions and notify on mobile Health: Monitor individual movements, location and workouts through the day using smartphone sensors like Proximity, Gyro, Accelerometer, GPS, Smart Cities: Monitoring parking spaces Monitoring pedestrian levels and vehicles to optimize driving and walking routes Weather adaptive and intelligent street lights Environment: Detecting air pollution and forest fire Early detection of earthquake & distributed control in particular places of tremors Wildlife tracking collar system to protect wildlife The IoT has become the buzzword in sectors like government, education, finance, agriculture, logistics and transportation. And it has made incredible strides in the consumer industry. While the concept is still forming shape, it has already transformed the way people, technology, and devices work.
Shark wins over Hive
Not long ago, ApacheTM Hadoop R (a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models) emerged as a solution to big data challenges. However, there were some inherent issues, related to performance and time lags as Hadoop is designed for batch processing and not for real-time queries. Another challenge with Hadoop is the requirement of `Map-Reduce’ perspective which was a deterrent for SQL engineers. To manage this issue, a data warehouse system called Hive was introduced. Hive wrapped the Map-Reduce nitty-gritty into an SQL-like interface with its Hive Query language. However, this did not resolve the inherent issues with Hadoop’s Map-Reduce approach i.e. latency. As a result of these challenges, open-source tools such as Spark, Impala and HAWQ emerged, and these tools leveraged techniques to reduce the latency associated with batch-based Hadoop jobs. Shark is one such Hadoop extension tool that speeds up both in-memory and on-disk queries. Impala, another such tool, works well with Hive/HDFS and resembles traditional parallel databases. With our passion for technology, we at Tavant, have tested these emerging solutions to evaluate their performance in real-world cases. Given below is our analysis of Shark: We simulated a total of six ad servers with a structured set of logs capturing the details of ad requests and deliveries. We generated 4 million requests in one hour per ad server, taking the size of logs on one server to 125 MB in one hour. We then set up two clusters – one with Hadoop/Hive and one with Spark/Shark. The same set of machine configurations was used for running both the clusters: OS: Ubuntu 12.04 LTS, Ram: 2GB, Number of nodes: 2 We executed a query to find out the number of requests, impressions and clicks based on the geographical location of the user. The following infographic illustrates the execution time recorded for both the cases: Thus, it can be inferred that Shark is superior to Hive in terms of performance. However, we witnessed a few issues with Shark: The memory size available to the Shark process must be chosen wisely, depending on the data size to be processed, in order to avoid ‘Out of Memory’ error. The improvement in the performance of Shark over Hive is not consistently greater by a constant factor. Heavy workloads and different queries may show less gap in the execution times of Shark and Hive. Nonetheless, Shark seems a good option at this point. Future releases of Shark will make available to us more features and upgrades. Don’t miss our next blog: `Evaluation of Impala’.
Analytics and Mobility are Tugging Brands into Digital Advertising
The exponential growth in the consumer base for smartphones and tablets is standing proof of the rapid migration of consumers from the world of broadcast, telecast and print media to the digital world. It demonstrates the increasing convergence of the virtual and physical worlds. Juniper’s Digital Retail Marketing Report “Loyalty, Promotions, Coupons & Advertising 2015-2019” has cited the reason for this migration to be the result of timely, targeted, personalized campaigns that enhance customer engagement. Cashing in on this trend, marketers are utilizing the advancement in analytics technology to create ROI enriched marketing campaigns. A forecast by eMarketer predicts that annual mobile advertising spend is expected to grow by more than two-fold by 2018 amounting to nearly $158.55 billion. This indicates fatter marketing budgets which is likely to grow bigger with time, as according to estimates, the global market share of total digital spends is expected to reach 30% in 2015 (Source: Magna Global). The following points highlight the impact and opportunity available for marketers today, owing to mobility and analytics: Maximized Personalization: Provides marketers with the ability to reach users with mobile internet, at the right place and at the right time. By using analytics, marketers can leverage consumer behavior, i.e. Leverage past activity (declared behavior) and interests (undeclared behavior for inferred conclusions by using predictive analytics. Emotional Connect: Content sharing has become easy and ubiquitous with social platforms blurring offline and online interactions. This essentially means brands can facilitate an emotional connection with the end consumer by curating content as per the needs of their target audience. Apart from this, it provides marketers with insights into customer reactions to their products or services providing them with valuable insight into customer preferences. Precise targeting: Abundant user data is available in real-time. This provides marketers with the opportunity to identify potential buyers and offer them impactful tailored content across different communication channels. For marketers to be successful, it will be important to plan seamless digital initiatives with campaigns that capitalize the entire lifecycle across screens and platforms rather than follow a silo model or a fragmented approach.
Right-Time Analytics in Mortgage Lending
The residential lending market has fallen from its peak and has settled at a more realistic area where it is most likely to stabilize in the $1 to $2 trillion mark for the rest of the decade. In the wake of the 2007 crisis, student loans have increased. The Millennials have piled up substantial debts and prefer to rent than buy. House prices have increased in major cities making it even more difficult to buy. Meanwhile, the cost to originate a loan is on the rise. And these are only some of the countless micro and macroeconomic trends currently impacting the mortgage lending sector. Alongside, technology innovations for the mortgage sector have made path-breaking strides to the extent where legacy applications are being replaced by faster, customer-friendly applications. While many companies are focusing on replacing or embracing their existing legacy systems, some of them are also diving deeper to get the best out of technology. These companies are using analytics to provide strategy, growth and revenue-related statistics. However, more often than not, many of these companies invest in analytics mostly to deliver reports to understand past behaviour and use that knowledge to improve processes and bridge existing gaps. The reports are usually sent to decision-makers on a periodic basis or delivered on demand. In most cases, the data is maybe a day old and is refreshed on a nightly basis. These reports serve the limited needs of the company to support its current operations. But to improve efficiency and reduce operational costs, it is essential to provide data at the time when it’s needed the most, not before and not after, this is called ‘Right-Time Business Analytics’. What is Right-Time Analytics? Information on important events which impact the business, have to reach decision makers as fast as possible. For example, if the employee attendance system detected an unusual sign-off for a loan officer who had to submit disclosures to customers on a particular day and if those disclosures have not been reassigned, then alerts need to be fired immediately to the second-in-command or the reporting manager, citing the number of violations that are about to happen. Such alerts, unfortunately, cannot be fired using traditional business intelligence methods where data is loaded into a data warehouse on a nightly basis. For each event like this, the gains may not be as visible to the human eye as it would be when the total number of events is calculated. Though organizations spend a lot of time measuring the average cost per loan, pipeline velocity and cycle time, very few lenders measure and assess the number of hours spent on closing a loan. This is where Right-Time Analysis comes in! Lenders who adapt to right-time business analytics will see natural improvements to operations beyond what is planned strategically. Another important real-time metric that would create a sense of urgency amongst the workforce is a bullet chart that clearly shows the real-time performance of the loans they are working on as compared to the set target and the company average. These are great tools that a company should consider implementing to improve turnaround times in addition to the other regular operational improvements. Social media is another area which benefits from analytics. Analysing user behaviour on websites is critical to detect user grievances and react to the same towards controlling the damage before it becomes viral. Implementing right time analytics along with effective activity monitoring helps identify several areas where operational improvements can be implemented, thus reducing the cost of originating a loan. In a stagnating market, mortgage lenders who recognize the value of Right-Time Analysis will stand to benefit in the short and long term. FAQs – Tavant Solutions How does Tavant implement right-time analytics in mortgage lending?Tavant provides real-time analytics delivering actionable insights at critical mortgage decision points, analyzing market conditions, borrower behavior, and risk factors to optimize pricing and approvals. What specific analytics capabilities does Tavant offer for mortgage lenders?They offer predictive analytics, real-time risk assessment, automated property valuation models, customer behavior analysis, and portfolio performance monitoring to improve decision-making. What are right-time analytics in mortgage lending?Delivery of relevant data and predictive insights exactly when lending decisions need to be made, including real-time market, borrower risk, and property valuation information. How do analytics improve mortgage approval rates?By providing comprehensive borrower profiles, alternative credit scoring, and risk assessment tools to identify qualified borrowers and optimize loan terms. What data sources are used in mortgage lending analytics?Credit bureau data, bank statements, employment records, property databases, market trends, social media insights, utility payment histories, and rental records.