But how can these modernization efforts be used for startups with smaller budgets? It pays to prepare for tomorrow today, and there are a number of measures that can help small businesses to embrace the future of winning and retaining customers.

Many of the approaches that can be taken today can help businesses to become more focused in their acquisition efforts and to gain greater insights from the data of their conversions.

(Image: Smart Insights)

The six pillars of effective digital marketing devised by Smart Insights offers an indication of how comprehensive digital transformation can be for the marketing efforts of businesses of all sizes, but they won't necessarily require wholesale changes.

In terms of conversational messaging content, media, and customer experience for instance, the emergence of big data can leverage powerful insights into who your target audience really is, the level of personalization they expect, and the type of content they want to digest.

But what measures can be taken today in order to modernize a startup's digital marketing efforts for tomorrow? Let's take a look at five key ways that lead acquisition can be enhanced with the future in mind:

Leverage Big Data

The voracity of big data means that it's become an essential and powerful marketing tool that can significantly enhance the customer experience. For instance, you could want to improve your customer onboarding measures through insights. Utilizing AI programs to interpret masses of visitor data, how they behave on your pages, and what key pain points are can help to illuminate where your website excels and struggles.

By adopting big data analytics, your startup will be capable of adding better personalization to customer-facing services-vastly improving their experience in the process.

These insights can also be adapted for future marketing campaigns by gathering emails through your website's lead magnet. This information can also be used for a greater understanding of what can inspire customers to enter your sales funnel. This insight into ‘why' as well as ‘how' can be invaluable for shaping self-perception.

The quality of insight that big data can provide can't be underestimated. It stands as a powerful marketing tool that can bring numerous advantages. It forms the foundation for reliable information built on research, automation, targeting, and personalization. Platforms like Google Analytics stand as strong low-cost services that can offer startups a great wealth on insight into the interactions between their website and its visitors.

Prepare for Zero-Party Data

Businesses with an eye on the future need to look beyond third-party cookies. In the age of GDPR, we're seeing more users become suspicious of sharing their data with businesses-and rightly so. However, this poses new challenges for the future of data acquisition.

Zero-party data is self-reported information, and is voluntarily shared with companies that are trusted by their audience.

To build impactful customer experiences, forward-thinking businesses are dependent on understanding what motivates their leads, and work to gain insights into these motivations first-hand.

The beauty of zero-party, self-reported data is that it's reliable, and the actionable insights that it provides can pave the way for revolutionizing the experience you can deliver for your customers.

Preparing for zero-party data today by incorporating subtle surveys and questionnaires on your pages and marketing materials can help to generate a larger bank of data should the negative sentiment towards third-party cookies continue to grow.

Work Now to Embrace a 5G Future

You need to incorporate 5G planning into your marketing strategy today. We're already accustomed to seeing digital ads appear on our smartphones, screens in shopping malls and airports, and online, but the arrival of 5G has the potential to supercharge digital marketing.

With connectivity becoming increasingly available from anywhere in the world-even in rural areas-businesses have more freedom to consider their digital advertising. Today, 5G ready smartphones are dominating marketplaces, making consumers more accessible through 5G advertising.

This means that small and ambitious businesses have more freedom to incorporate creativity into their marketing strategies. With some brands already working to develop advertising in the metaverse and via augmented reality cameras, the sky seems to be the limit with what marketing can achieve in the coming years.

With this in mind, it's essential that you incorporate 5G preparedness into your strategies, and look to the opportunities that more high-quality campaigns can bring in terms of lead engagement and acquisition.

Furthermore, faster data means that its collection is likely to improve significantly in the 5G era. Finding out more about your customers will pave the way for more responsive personalization, with experiences capable of being seamlessly tailored to the needs of customers.

Embrace Video

According to a report from Technology Advice, fewer than a quarter of businesses surveyed claimed to use video in their marketing efforts. However, this is a faux pas when considering the popularity of video for consumers-particularly those who are prevalent on social media platforms.

In fact, an Animoto survey found that four-times as many consumers prefer video as opposed to reading about a product. Today, technology is making video-oriented campaigns more advanced and high-quality-without the need to turn to professional editing teams and choreographers.

Given how easy it is to create video content, small businesses have the power to create impactful marketing campaigns that are far more likely to get noticed by customers and acted upon.

Use Advanced Tools to Your Advantage

When you've strategized your modernized marketing goals, it's essential that you utilize the right tools to help you to achieve them. Luckily, there are plenty of great options that are low-cost for startups to get started with their strategy.

Online software like social media schedulers, for instance, can help to provide analytics to keep track of what your audience is engaging in and what they're largely ignoring. The aforementioned Google Analytics is a highly advanced tool that presents wide ranges of data that's open for interpretation.

For more specialist marketing tools, there's HubSpot Marketing Hub, which helps users to consolidate all their marketing tools into one single platform, while the likes of Trello and TrueNorth all work wonders in providing campaign management.

Although the digital marketing landscape is constantly evolving, recent advances in technology promise to be a watershed moment for an industry that's always ripe for further innovation.

As the potential of 5G and big data are further realized, we're likely to see a new flurry of ambitious and advanced campaigns designed to personalize experiences, engage, and entertain audiences.

By planning to accommodate these technologies today, your startup will be capable of reaping the benefits faster tomorrow.

The post Scaling the Marketing Efforts of Startups: 5 Essential Ways to Modernize Your Lead Acquisition appeared first on Datafloq.

Funding/Lack of Resources

Lack of resources has been named the leading challenge nonprofits faced in 2019. This is something they share even with for-profit businesses. An inadequate resource pool is a multifaceted problem that needs to be tackled from multiple fronts. The two main contributors to not having enough resources to effectively operate are difficulties with donor acquisition and retention and the high turnover of fundraising staff. So how can journey mapping help you address these challenges? Let's have a look.

Donor acquisition and retention

A donor journey map helps your operational and executive teams understand the full donor experience across the lifecycle stages, channels, and touchpoints. Donor journey mapping is the process of designing, outlining, and charting the engagements, interactions, and activities a donor has with your organization. The journey map visualizes all the interactions a person has with your not-for-profit as well as the internal or external influences affecting his or her behaviors. Such a map can vary in detail and complexity, depending on what you want to chart on it, from a donor experience following an acknowledgment when they make a gift to a year-long onboarding plan for new donors.

Such a comprehensive blueprint allows your non-profit to identify opportunities to improve the donor's experience and drive more value for the organization. In the current competitive environment, where the number of non-profits is increasing every year, more and more organizations are competing for donor money and resources. Without a clear understanding of how your organization creates value with and for donors, what their requirements and aspirations are as well as how you can optimize your donor experience, you are running at risk of being left behind. Research shows that brands that manage their customer journeys outperform those that don't.

Donor-centered fundraising is about putting your donor first, looking at your organization through their eyes, nurturing positive relationships with them, and ultimately increasing their loyalty and exceeding your fundraising goals. By creating your donor journey map, you gain invaluable insight into who your donors are (donor persona), align your internal teams to optimize, and build a more meaningful connection with your donors, thus improve your donor acquisition and retention.

Talent Retention

Transitions in staff is another huge challenge non-profit organizations face. Here they compete with both commercial and other non-profits as well as the changing job market. This is why understanding your employee experience and making it more positive is imperative to help ensure stability in staff recruitment and retention. And here is where employee journey mapping comes to the rescue.

Employee journey mapping is a method to help ensure your employees have positive experiences with your company from their first moment forward. Much like a donor journey map, an employee journey map is a blueprint of end-to-end interactions that an employee has with your organization. Such a technique helps you evaluate employee experience and identify areas for improvement.

A more satisfied employee is a more engaged and loyal employee. According to research, staff with lower engagement are four times more likely to leave their jobs than those who are highly engaged. Such a high turnover rate comes at a high cost, amounting up to 199% of a salary cost. For non-profits, these numbers might be even higher, as they can lose donors and volunteers who work closely with those employees who decide to leave your organization. In order to ensure your employees are engaged and stay with you for a long time, you need to know what makes them happy. Creating your employee personas is another tool you can use to get to know your employees better.

An employee persona is a made-up person, who is created based on your real employees. By learning about your employees' traits, values, experiences, aspirations, and pain points, you can work on matching their values with organizational values. By creating an employee journey map and acting on the insights you get from it, you can retain your organization's most valuable assets and secure your future growth.

Improving client experience

Ultimately, the goal of any organization is to consistently satisfy its customers and increase its customer base. For a non-profit, this comes down to serving your service or product recipients the best way possible. In order to do that, you should know your customers' needs and goals well and ensure that your organization meets them. And customer journey mapping is an invaluable tool in this process. A customer journey map helps your internal teams put the customer first, hence create a more relevant customer experience, increase your productivity and improve resource distribution. In turn, this will help you identify ways to increase your efficiency and accomplish more with less.

Conclusion

No doubt, non-profit organizations face a lot of challenges. Competitive landscape, external influences out of your control, new players in the market, bringing in new requests and standards, make donor retention and employee engagement increasingly harder. To thrive, non-profits need to shift to a more people-centered orientation, putting their donors, employees, and customers first.

Customer journey mapping is an invaluable tool that can help your company go through this transition faster and come out the other side with more value to offer to all your internal and external stakeholders.

The post How Nonprofits Can Leverage Journey Mapping to Solve Their Challenges appeared first on Datafloq.

Over the last four years, the use of AI among enterprise businesses has increased by 270%, to the point that most customers handle most of their interactions with an online business without communicating with real people.

With that said, read on to learn more about five key benefits AI-enhanced CX technologies can offer your business when it comes to improving the online experience for your customers.

Image: Gerd Altmann from Pixabay

1. Gain a better understanding of your customers

One of the biggest reasons to embrace AI technologies for interacting with your customers (such as chatbots) is because of the remarkable insights they provide into customer demands and needs.

Through AI and machine learning, popular CRM and CDP programs can gather and analyze incredible amounts of data about specific customers. These programs can specifically analyze your customer's social, historical, and behavioral patterns, allowing you to market products and services to them more effectively.

Unlike other forms of data collection, AI technologies continually learn, which allows them to constantly improve the data they have collected. For this reason, AI can help you to anticipate customer behavior, allowing you to provide more relevant content that will encourage and motivate them into action.

This information can also increase sales opportunities by streamlining the customer's journey, guiding them from initial interest through to conversions. For example, AI can determine what similar customers are buying, automatically providing relevant recommendations.

2. Improve customer service and lead generation

Through AI-enhanced CX technologies like chatbots, you can quickly and easily improve the quality of your customer service. This is because these programs have access to vast amounts of customer information, allowing them to identify common issues that your audience had and provide them with relevant and useful solutions quickly. Unlike a human customer service representative, a chatbot can often predict a customer's problem before they even explain it, saving you and your customer time and energy.

Image: Andrea Piacquadio from Pexels

SaaS help desks are another example of an AI-enhanced CX technology that can generate new and more relevant leads for your business. As well as gathering crucial data about specific customers and gaining insights into the types of products that they like, these helpdesks can also help your customer service team manage daily support requests and offer time-saving features such as systems that store common questions and responses, eliminating the need to answer the same questions over and over again.

3. Achieve 24/7 results and save money

Another significant benefit of AI-enhanced customer experience software is that it works around the clock. Unlike human employees, it doesn't need a break or a day off and never makes mistakes. The best part is that AI technology is cheaper than paying an employee salary and therefore provides a better return on ROI.

With that being said, AI isn't designed to replace human employees entirely. Instead, it handles repetitive, mundane tasks that keep people busy but don't grow or expand your business. Therefore, it helps to prevent employee burnout, eliminates busywork', and ensures maximum productivity.

Image: mohamed Hassan from Pixabay

4. Take productivity to the next level

AI-enhanced CX technology can also respond immediately to customer inquires, no matter the time of day. This can make the difference between a simple question answered and a long-drawn-out customer complaint. It can also provide customers with automated updates such as delivery or itinerary changes.

When they encounter a problem they can't manage, AI-based CX programs automatically transfer the customer to a live representative. This means your team will only be handling more complex queries, allowing your programs to focus on simpler matters in the meantime.

AI can also proactively begin conversations with your customers, providing them with information about products and services and increasing cross-selling opportunities, which further reduces the number of calls and emails to your customer support team.

5. Enhances email content marketing

Like many businesses, you probably devote a lot of your time to email marketing. Without AI, however, even the best email marketing programs miss the mark. This is because AI makes it easy to refine your approach, increasing the odds of delivering effective and relevant email content to the right customers at the right time.

Email marketing software that is enhanced with AI and machine learning offer advanced features such as algorithms that can record customer data points, including email browsing habits, online browsing experiences, and other ways to interact with the content you provide. According to online marketer Alexander Williams of Hosting Data, these kinds of features are worth the extra cost you'll pay for them, saying You have to settle for a lack of advanced features on the free plan, which is pretty much the trend with every premium email marketing service tool…but take note just about any premium or paid service will get you closer to where you want to be business-wise.

This information provides amazing insights into the kinds of things that your customers are likely to respond favorably to and detects content that is especially relevant to specific niches of your target audience, allowing you to create uber-personalized email messages.

Conclusion

Regardless of the nature of your business or the size of your company, artificial intelligence and machine learning are powerful tools when it comes to customer service. From collecting invaluable data and insights from your customers, to streamlining and responding to common customer requests, to getting personal with your marketing, AI-enhanced CX technologies can provide business.

The post AI and Customer Experience: 5 Benefits of AI-Enhanced CX appeared first on Datafloq.

The post Your Complete Guide to a Obtaining a 360 Customer View appeared first on Datafloq.

If you answered yes' to all or some of the questions above, you are in luck. The widespread use of social media apps like Facebook, Twitter, Facebook, and WhatsApp, as well as the rise in social media groups and pages, is an indication of the fact that e-commerce is a huge game changer for businesses. It is the one thing that could boost your sales this year. In this article, we look at everything you need to know about big data and how you can leverage it for the success of your online store.

But first, what is big data?

Big data refers to large datasets stored and analyzed using the latest technologies to offer meaningful insights into your business, and also to guide your decisions. This brings us to e-commerce analytics, which refers to the processes involved in the collection and the analysis of online activities on your app or site. So, it's clear that you could use big data to scale your e-commerce business.

It's also important to understand big data analytics these are the processes involved in the examination, analysis, and uncovering of the hidden data patterns, also from big data. Thanks to big data analytics, you obtain pieces of information like market trends for e cigarettes or customer preferences.

But, before we look at how big data will help your e-commerce business, do you have the right or any data? Do you collect/ store data? Because you must have data. Many retailers fail in business because of lack of data, but you cannot be in that category today. Besides knowing the importance of data, you also have access to the best of backup disaster recovery tools should anything happen to you. Companies like Propel Technology could help, but you also need to protect your data at all costs.

Now then, how can you use Big Data in e-commerce?

1. Provision of a personalized user experience

If properly utilized, your customers and site visitors can now develop a positive relationship with your brand. By analyzing the products visitors have purchased or searched for in the past, it's easier for you to recommend items appropriately. Big Data allows you to track the activity of your site visitors, allowing you to personalize your recommendations. Big data is that thing that makes everyone on the internet or social media wonder if the internet can read minds.

2. Prediction of trends

Like your competitors, you want to know about the next best-selling product, and you want to find this information before your competitors. Thanks to big data, you can find this information. Big Data Analytics involves the use of trend forecasting algorithms which eliminate the guesswork out of predicting the next big trend. These algorithms comb for data from your audience's social media posts and their browsing habits and lead you to the next best thing.

There also is the analysis of ad-buying data which guides you to find out what the marketing departments in your industry are pushing for. Predictive analysis of trends also involves sentiment analysis that determines the context in which a product is being discussed online and whether they are positive or negative.

3. Price optimization

Thanks to big data, you can easily identify the best prices for your goods you do this easily by tracking conversations and specifics on transactions, cost of goods, and your competitors, among other variables. Also, big data allows tracking of the rise or fall of demand with regards to pricing.

4. Forecasting of demand

You don't want to stock more of an item as its season runs out. Big data helps you navigate this challenge by using your historical data. Inventory is expensive, and you need accurate demand forecasting.

5. Optimization of customer services

Thanks to data collected from social media, you will have a full view of your customers‘ opinions, preferences, and needs.

6. More sales

By offering a more personalized shopping experience, you reduce the abandonment rate at the cart by learning more about your customers and offering options that best fit their needs.

Therefore, it's an undeniable fact that big data is a huge game changer in e-commerce. Used appropriately, this technology helps in driving more strategic action, and it enhances customer experiences.

The post Why You Must Leverage Big Data to Boost the Success of Your E-commerce Business appeared first on Datafloq.

Adopting AI-enabled processes may be difficult in the beginning, but in the long, it offers affordability alongside increased productivity and profitability. The introduction of AI into an organization is something that can allow a business to find new and innovative ways and here, we highlight eight benefits of introducing AI to an organization.

1. Saves money

Automation is highly cost-effective as a long-term solution because machines are capable of completing tasks at a faster rate than humans. This allows people to use their skills and time for other things in the business because machine learning automates the growing swaths of mental labor.

Tasks can be automated when a certain task gets broken down into smaller tasks, and machines can perform them in a shorter length of time. When organizations can pass more tedious tasks to machines, employees can focus on more complex tasks, improve their skills set and innovate new ideas to grow the business.

In some areas, the need for human labor and physical resources can be completely removed resulting in saving costs on salaries and resources.

2. Improved and streamlined relationships with clients

Central to a business is a good relationship with clients, which simply stems from good service and establishing a relationship of trust and loyalty. Certain operations such as 24/7 online support require AI to operate at any time of day as well as deal with high customer volumes.

The vast improvement of internal operations also contributes to optimized service delivery. For instance, organizations can use software like Spark to improve the effectiveness of processes like scheduling, abstraction, machine learning, and more.

For organizations that use different programming languages or those that need coordination of application runtimes, Hadoop is an excellent choice. A business might consider using technologies like Hadoop and Spark, along with other AI tools, can assist in streamlining processes.

3. Enhancement of products and services

Every business needs to stay a step ahead of their competition and innovating improved products and services keep the market looking forward. AI has the potential to allow a business to add improvements to its products and services, such as virtual features and automation.

The improvement of products and services also heavily relies on data and AI has the capability to process data with minimal errors. It also becomes easier to make decisions based on statistics and accurate data.

4. Improved employee efficiency

AI allows employees to diversify their input into a business and improves efficiency as some tasks are either taken over or improved by incorporating AI. Tools such as virtual assistants reduce the need for additional labor in the form of assistants.

It has become so popular that voice assistants in the future may start employing voice-biometric authentication, use them for producing translations and transcriptions of meetings, and more.

The growing concern of AI taking over jobs in an organization is one of the main reason adoption becomes a challenge. However, most AI technology continues to rely on human interaction to operate optimally and it is proven that clients and customers often prefer human interaction.

5. Encourages employee creativity

AI eliminates a large portion of tedious and repetitive tasks that frees up the employees to focus on other tasks that add value to the organization. When an employee doesn't have to do tasks that AI technology can perform, they would have the time and energy to think more creatively, especially when trying to resolve workplace challenges.

While a lot of people worry about getting replaced by AI, the fact is, experts and analysts predict that AI can potentially create more jobs in the future. This benefit of encouraging creativity stems from the fact that employees can focus on the more innovative and interesting aspects of their jobs as technology takes over the simpler, routine tasks.

6. Improves sales and marketing

In business, sales and marketing generate statistics regularly – and these statistics are the best way for analysis with algorithms of machine learning. This is one of the “repetitive tasks” that AI can manage by processing data faster than humans, which, in turn, allows employees to see the results faster.

This allows employees to devise strategies to boost their sales and focus on marketing campaigns for the benefit of the business. Digital marketing has also shown the benefits of AI-driven marketing, and there are various tools that allow for the automation of marketing campaigns and simple ways to track analytics.

7. Minimizing errors and detecting defects

Machine learning and AI technology help workers deal with issues that seemed impossible to solve before integrating the technology. AI allows easier ways to track tasks and to be able to retrace one's steps in the event of an error or a glitch.

The shift from analog is necessary for business operations as businesses are increasingly under pressure to be more accountable and transparent. AI adds value to the strategic operations of an organization and vastly improves credibility.

8. Helps with decision-making

Most businesses rely on data to make decisions that will greatly impact the future of the business and accurate data ensures that the business operates optimally. Automation and digital migration allow for strategies that decrease the chances of business operations collapsing due to human error.

The larger the business, the larger the data collection and this requires accurate methods of calculations, which can usually be achieved through AI and human assistance.

Conclusion

AI is here to make inroads into the key processes and it's time for organizations to start recognizing the benefits AI has to offer. One of the stumbling blocks preventing businesses from fully implementing AI-driven processes is the misconception that it will result in job loss and less need for human resources. If applied correctly, AI has the potential to transform and streamline businesses to the point of creating new jobs.

The post 8 Benefits of Being an AI-Enabled Organization appeared first on Datafloq.

Punching the Clock

Since the first employer hired the first employee, tracking hours worked has been a major headache. Done by hand until the advent of the first punch clock, it was easy to fudge hours worked. The punch clock eliminated the worst of the games, but not all; friends would clock in someone running late, to keep them from losing pay, and conversely, clock them out if they had to leave early. Punch clocks also did nothing to eliminate the drudgery of pulling cards, totalling hours, figuring out rates of pay to apply, and getting it all into the payroll department. Automating the time clock erases these problems; the time clock is programmed with all of the information needed to calculate total hours, shift differentials, pay rates, and overtime. This information is sent to payroll automatically for processing.

Automated time clocks work off of badges containing ID chips, which are scanned when the employee arrives to start work, and are scanned again when they leave. Badges are also scanned anytime the employee leaves the work area – for work breaks, or approved absences like doctor visits.

There are also software-driven time clocks, which work by having the employee log in or log out of an application, instead of physically scanning a badge.

Paying the Bills

Accounts payable is a major endeavor, regardless of your business's size; tracking purchases and invoices from vendors is a full-time job and then some. Automating the process is both a time and money saver for your company.

It's no small task to convert from a manual AP office to automating the process; you have to examine all of the steps involved, identify exception processes, and get buy-in from your vendors. To totally automate AP, vendors have to submit invoices electronically, and this requires changes in their processes as well. As automating AP usually results in faster payment, vendors are usually eager to hop on board. However, there will always be exceptions, and you will have to incorporate them into the workflow.

Billing the Customer

Accounts receivable is, traditionally, an overhead expense. Automating your invoicing turns this expense into an asset.

The benefits to automating your invoices are numerous: you get invoices out faster, resulting in faster payment; by converting your invoices from paper to electronic, you get a database of information you can mine easily; disputes are resolved faster when turnaround time for invoices is reduced from weeks down to a day or two. There are others, but you get the drift.

Mining data from your customer invoices drives product development you can determine which products are selling well and which ones are not; this results in decisions to stock a product or drop it from your offerings. By determining product desirability, you can then decide what future products you should consider selling.

Paying the Staff

Payroll is one of the biggest headaches and expenses any business, small or large, has to deal with on an ongoing basis. Many businesses find producing payroll in-house to be too much sugar for the dime, as the saying goes, and they outsource it to third-party processors, such as ADP. However, you have to have the data to give your third-party processor, and you have to give it in a timely manner, or your staff will not be paid, and nothing sparks rebellion like not getting your paycheck on time.

Automating your time-keeping processes is the first step to automating payroll. The data from the time clocks are processed into a payroll file, either for your in-house application or that third-party processor. You have to add information from each employee's personnel file into the data, such as pay rate, pay classification such as hourly or salaried, and tax rates. Once completed, this file is provided as input for the payroll program or the payroll processor.

Payroll is obviously one of the most common and important tasks, both to employees and business owners. Go with a trusted provider – if you mess this up, you're definitely going to be the least favorite guy at the office for a while says Logan Block, Director of Content at Sleepopolis.

When the payroll file is processed, checks or direct deposit tapes are cut and sent out, and your staff is compensated on time.

Dealing with the Customer

Customer service is at one time the most important department to your business, and the most neglected. Many businesses treat customer service as an afterthought when it should be the first thing on everybody's mind.

Ultimately, dealing with the customer needs to be considered of utmost importance. It is important for businesses to show that they truly care about their customer's needs and not just their bottom line says Michael Dadashi, CEO of Infinite Recovery

Giving good customer service is a problem for most companies, and until they resolve it, they can have a high dissatisfaction rate among their customers. Automating customer service management is the first step to having healthy relationships with paying customers.

Managing customer service calls is a challenge, and managing the trouble tickets generated by the calls only adds to the difficulty. Customer management systems can reduce the efforts required of your customer service staff, by automating the tracking of the calls and the generation and tracking of the tickets.

Customer management systems utilize a customer database, containing information on your clients. They also produce a database of customer calls and tickets by customer. Tracking the tickets lets you analyze whether or not the customer is calling with valid complaints. If so, the tickets let you know where to change your processes to eliminate or at least reduce the issue. If not, you can use the information to make managerial decisions about the customer.

Final Thoughts

Today's business world is fast-paced; keeping up with the demands of doing business in such an atmosphere is stressful, both to the business owner and the employees. Help everybody have an easier time doing their jobs by automating as much as possible, giving them the time to interact with your customers at a human level whenever possible.

The post 5 Ways Small Businesses Can Maximize the Benefits of Automation appeared first on Datafloq.

This process has accelerated even more with automation and machine learning taking over the world. Even though all we've learnt from sci-fi movies is the breakthrough of technology that leads to doomsday, we're far from there.

We're still living in the age where a large number of applications of technologies like machine learning go unseen. One such area is marketing.

For those who are utilizing it, know that machine learning can be the difference between driving results and losing customers. Research indicates that 74 percent of the organizations believe that their goals can be better achieved with investment in machine learning. With data becoming more and more accessible, marketers are realizing the potential of machine learning for bridging the gap between brands and their customers.

Customer profiles now go beyond names and demographics. Marketers in today's generation have access to customer personas. They have all the information right from device preferences of the customers to social posts, browsing and content history, interests among other things.

However, having all this data makes it much more difficult for the marketer to build campaigns, form strategies, create user segments etc. Mastering this data for the task of engaging and retaining customers becomes even more complicated. But, with machine learning, marketers can finally build meaningful connections with their audience based on valuable data.

In fact, data can be the difference between running front and getting thrown in the cut-throat market competition. Thanks to machine learning, marketers have ways to utilize it and get ahead in the race.

Let's take a look at exciting ways how machine learning development is narrowing bridges between customer and brands

Forming better customer segments

Marketers know the pain behind manually keep a track of all customer data points. Not only is the task incommodious, but also leaves a significant chunk of customer data underutilized.

The inclusion of multiple parameters makes it difficult for the marketer to decide which ones to pick and in what quantities to segment customers. Not to forget that incorrect customer segmentation is one of the top reasons why customer churn rates increase.

However, machine learning backed customer segmentation can analyze your user base and find correlations between different parameters. This practice takes your personalization to an altogether different level. In other words, the better your segments are, the more valued is your relationship with your customer.

Predicting customer's behaviour

Predictive analysis is one of the best applications of machine learning. It has helped brands understand a holistic view of their customer and devise campaigns for their next course of action.

Considering the market competition today, a business's performance relies on its ability to predict the demands of the customers at every stage of their journey. With machine learning to the rescue, brands are already acing it.

Companies like Amazon have been predicting behaviours for years now. Notice its product recommendation engine that takes people‘s past behaviours into consideration for determining their future needs. This practice is also responsible for driving 55 pecent of its sales.

Polishing selling strategies

Making a move in your cross and upselling strategies can be difficult for customers. It is like walking on a tightrope without being disturbing the balance.

To accomplish it flawlessly, marketers can need to mine into data. They need to find out the products have been brought together, the segment of customers who prefer a certain kind of product, the products people love to splurge on and more. Understanding all this enhances the customer experience.

Machine learning, on the other hand, can act as a catalyst to this cumbersome task. It assists in data-based product recommendations and helps in reaching out to the customer at the right time.

Identifying the right engagement channel

We're now in a world where multiple paths exist to reach a particular brand. For a business, there are customers scattered on different platforms. Furthermore, the brands who reach out to their customers with the apt content on the right platform, make all the difference.

Identifying the engagement channel is fundamental to any brand. This can help identify customers who are receptive to a particular channel and campaign. Using machine learning solutions, brands can answer these questions and deliver their campaigns at the right time to their customers.

When the brand Homestay started using machine learning, it was able to identify the customers who see their ads. This led to a 46 percent increase in their gross revenue since they started spending less on the wrong people.

Becoming a leader

To answer a question like what separates Amazon from a medium enterprise, one needs to take a look at their leadership. Becoming a leader isn't something that one can accomplish in a day. It requires taking the right decisions at the right time. When it comes to marketing, a leader is one who can make data-backed decisions.

The right marketing activities, when linked with business goals, lead to an upward growth trend. Machine learning in such a scenario can help exercise better command on your customers with intelligent solutions. Be it chatbots for customer service or curated timelines for customers, ML is aiding one become a leader in the market.

Conclusion

Brands all across the world are using machine learning to devise their marketing strategies. Gone are the days when marketers built campaigns based on intuitions. Today, as the world moves forward customer's purchase habits are changing more than ever. Unless brands have ML solutions to help make suitable decisions, they will continue to limit their potential and not even know what they're missing out.

The post How Machine Learning Is Bridging the Gap Between Brands and their Customers? appeared first on Datafloq.

• Those customers who click away have an estimated spending power of ‘ 11.75 billion in the UK alone. This is approximately 10% of the total UK online spend in 2016.
• 82% of customers with access requirements will spend more if websites were more accessible.

Web developers design websites with a focus on delivering appealing visual components to satisfy their clients. However, they tend to overlook the need to include web accessibility components. Users with disabilities, therefore, shun disabled-unfriendly websites, thereby increasing website bounce rates.

Websites must be equally accessible to all users, and AI has already begun taking part in this important mission. Most business owners are unaware of website accessibility laws and that failure to comply with the Web Content Accessibility Guidelines (WCAG) will result in losing a major segment of potential customers as well as serious litigation. It should be noted that in 2018 alone, 2,258 website accessibility lawsuits were filed in the federal court.

Maintaining compliance with Web Content Accessibility Guidelines (WCAG) helps businesses build brand loyalty with their disabled clients. Accessible websites contribute to an augmenting customer base through their benefits of usability and search engine optimization.

According to the Pew Research Center, 50% of disabled Americans are less likely to use the internet daily when compared to 79% of users who are not disabled.

Despite stringent acts like the ADA, several websites remain non-complaint. Web developers must consider automated, AI-empowered web accessibility tools like accessiBe. This groundbreaking tool automatically applies accessibility standards to websites, making them accessible to users with disabilities.

The AI-based solution scans websites, incorporates the required modifications and transmits accessible content best suited for users with disabilities. They also re-scan and work daily, a feature advantageous for dynamically changing websites.

How AI Helps With Digital Inclusion

AI has enabled easy access to information for users who have sensory, physical or cognitive impairments. AI helps by enabling disabled users to proactively interact with the web in the following ways:

1. Improving Website Accessibility

Alt text empowered by Artificial Intelligence automatically writes captions for the blind and the visually impaired. This form of text helps users with visual disabilities understand an image and its components. Without the inclusion of AI, users can hear only the word “image” without a description of its details.

Facebook uses AI-enabled automatic alt text that helps blind or visually impaired users feel connected and included. According to Facebook, 2 billion photos are posted across social media platforms and with nearly 39 million blind users and 246 million users with severe visual impairment, this AI-enabled automatic alt text helps them to make the most of Facebook.

Automatic alt text is based on object recognition technology built on a convolution neural network that has been tuned to millions of learnable parameters. When a visually disabled user accesses the screen reader on an iOS device, he can listen to the list of items in the photo on the Facebook page when he swipes past it. Earlier, users were only able to hear the name of the person who shared the photo. With automatic alt text being based on AI, users obtain access to a richer description of the photo.

“Think about an eCommerce website with tons of banners that include text in the form of offers and promotions, notes Shir Ekerling, Co-Founder & CEO of accessiBe. Blind people completely miss that kind of text messaging if they're not described manually word-by-word, image-by-image. However, it's practically impossible to manually keep track of every image on a given website. The object recognition and O.C.R (optical character recognition) technologies we utilize help blind people use websites on a daily basis.”

The learning element of the neural network detects images and visual concepts. It splits the image into three broad groups of people, objects, and scenes. The alt text details the number of people and their actions followed by the number of objects in the image. It also describes the settings and scenes detected in the image.

2. Opening Newer Channels to Access the Web

Voice interfaces have become common, but they aren't equally accessible. A user with a speech disorder due to a neurological impairment like ALS or multiple sclerosis may not be able to use Google Assistant or Amazon‘s Alexa.

Google's Project Euphonia can make speech technology more accessible to disabled users. It uses AI to improve the capability of computers to understand diverse speech patterns that include impaired speech. Voices of people are recorded and used to optimize AI algorithms so that they can reliably transcribe words. Google software converts the recorded voice samples into spectrograms that are used to train the AI algorithm to identify this less common form of speech.

This collaborative initiative by ALS Therapy Development Institute (ALS TDI) and Google will help users who cannot speak or have physical disabilities access the web independently by detecting gestures and sounds.

3. Boosting Customer Engagements

AI helps customers with disabilities to deeply engage through ways like:

• Text Summarization

Web accessibility solutions needn't be limited to speech, visual, and mobility concerns. Users with different grades of cognitive impairments or learning disorders also need help to access the web.

Text summarization is a tool that compresses a huge amount of information. It helps people with cognitive impairments such as dyslexia, attention deficit disorders, and memory issues.

Salesforce has developed an AI-based abstract summarization algorithm that condenses longer forms of text. This model uses deep learning neural networks to interpret content and introduce the right words to produce an accurate summary. This tool is based on the automated evaluation metric known as Recall-Oriented Understudy for Gisting Evaluation (ROUGE) that updates itself with higher scores for better summaries.

These AI-enabled text summaries are accurate and can help users with cognitive issues keep up with the deluge of information on the internet.

• Lip-Reading

Providing closed captions can help expand the customer base for video and audio content.

The internet has a deficit of disabled-friendly content. Google's DeepMind was developed based on AI's lip-reading algorithm. This system can generate closed caption content for deaf users that helps the hearing impaired easily interpret visual content and improve web accessibility.

Google's DeepMind was trained based on 5000 hours of six different television programs. This system successfully identified 17,500 unique words. It can outperform professional lip-readers by translating 46.8% of words without errors. The technology can enhance hearing aids, support silent dictation in public places, and facilitate speech recognition in a noisy environment.

Wrapping Up

The above-mentioned AI technologies support users with disabilities to easily access the internet for their needs. Developing accessible websites will help business owners attract and explore a newer segment of customers, drive traffic and increase sales.

The post 3 Ways AI Is Making The Internet More Accessible appeared first on Datafloq.

In order to figure out which specific marketing campaigns are delivering the best results in terms of lead generation and conversions, an attribution model is often used to track links and other marketing tools to record interactions. However, when it comes to mobile marketing, the traditional attribution approach is not always perfectly accurate.

The reason why mobile attribution is a totally different ballgame than traditional marketing attribution is because of its complexity. It is far easier to track a customer's journey on a desktop version of a website by using cookies, image tags, and customized URL parameters. However, this is far more complicated on mobile devices, particularly if a customer is switching between the mobile website and an installed app.

Unfortunately, many marketing teams struggle with proper attribution when it comes to mobile interactions because they do not understand how to track their campaigns properly. The good news is there are some specific mobile app attribution techniques which can make things much easier and far more accurate, too.

Let's discuss.

Use Multi-Touch Attribution over Single Touch

There has always been some disagreement over the best attribution model to use in marketing. According to a study conducted by Bizible, the numbers are fairly evenly distributed regarding the types of touch models that marketing teams use for attribution.

The most popular form is lead conversion touch, followed closely by last touch and multi-touch. It should also be alarming to note that 34% of teams do not follow any attribution model at all meaning that they are shooting in the dark to determine which marketing channels are driving in the most customers.

However, a customer's identification can actually be lost as customers switch between a mobile website and the app. There are several reasons for this, but one major reason is due to the fact that Apple blocked the ability of cookie tracking within apps with the iOS 11 release.

While single touch approaches may be appropriate for easily trackable marketing campaigns (such as emails, PPC ads, or external links), the path from the initial interaction to conversion becomes far more muddled on mobile app devices.

Attribution relies on creating unique customer accounts, which is used as data source information for an integrated CRM system. But, since these cannot be traced when a customer switches to an app, a multi-touch mobile attribution model must be followed for accurate metric reporting.

Use Varying Methods of Measuring Attribution

Another important difference between traditional attribution and mobile app attribution is the methods of measurement. Again, customers are normally tracked through cookies which are associated with a unique customer account when they interact with online marketing content. This works well for single touch and multi-touch approaches, but once again, mobile app attribution makes things a bit more complicated.

Studies have found that new app users convert after an average of 2.7 advertising sources. Therefore, marketers should use multiple attribution measurement methods to keep track of each individual's interactions.

There are four main methods for this:

1. Unique Identifier Matching

This method is used for an app to app tracking, meaning that each app installer creates a unique identity that can be tracked by an attribution software system. This follows a user's journey within app systems only not on websites.

So, say that a customer is scrolling through their Facebook app and comes upon an add which leads to an install page to your company's app. This interaction would be tracked through unique identifier matching.

2. Device Fingerprinting

Every mobile or tablet device will have a unique ID number that attribution software can use to track a customer's journey. This is an automated approach that will match up a device's unique ID number to a customer's account, matching up the unique identifiers, such as their IP address.

This is done by redirecting a user from a tracked link and collecting available identifying data, such as HTTP headers, from the device they are using. This is the most popular cross-platform attribution model.

However, it is not always totally accurate. It can sometimes lead to false attribution if a user is using different devices or if two separate users have the same identifying factors, such as location or device used.

3. Open URL with click ID

This is probably the most simplistic and straight-forward approach for attribution. When a customer clicks on an advertisement, they are assigned a tracking ID. Each sequential click following the initial one is then attributed to the same account, with the initial advertisement receiving attribution.

4. People-based attribution

Finally, the fourth model is a combination of both app-to-app installs and mobile website to app installs. Unfortunately, this is incredibly difficult to do – since both mobile and web interactions play key roles in the modern customer journey.

People-based attribution tries to connect both a device's web cookies and unique identifiers within an app to correlate to a single user across multiple platforms. This approach requires deep link tracking through Big Data and AI resources to match up multiple interactions to the same unique user account.

Tie in Attribution to the Customer Experience

Attribution data matters for several reasons. Many marketing teams use it to optimize their resources. For instance, if one specific campaign is not performing as highly as another, funds will be re-allocated to focus on the more successful channels.

However, this data should not just be used for lead generation purposes. At the end of the day, a company is not successful just because they have a great advertising strategy. It is because they offer their customers the best experience. Therefore, attribution data should be applied to the customer experience (CX) whenever and however possible.

One way to do this is to use attribution information to create customer journey maps that help you understand what is working best to influence conversions. By understanding the general path that customers follow from their first ad interaction to final conversion, marketers can optimize app layouts and CTA placements to ensure that customers can easily reach their intended destination across every device.

Conclusion

Mobile app attribution is clearly not a simple task to accomplish. It is highly complex and requires lots of careful data analysis, as well as sophisticated technology to track customer interactions for proper attribution.

However, it is important for marketers to understand the why and the how behind each approach so they can optimize their own attribution methods and apply what they find to the most important element: the customer experience.

The post Your Mobile Marketing Data Is Dirty – But These Mobile App Attribution Techniques Can Help appeared first on Datafloq.