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The Enormous Power of AI and Chatbots for …

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By Alice Berg

The bots are here and they here to stay. See, despite the chatbot phenomenon has gained ground only a few years ago, it has since become a full-on revolution worthy of the attention. In fact, by 2024, the bot market size is expected to exceed $1.34 billion. And as you ponder on that, it is also important to note that in 2019, at least 40% of large business ventures will implement the use of chatbots.

Let’s take a look at some AI applications in business in 2019 and beyond.

Chatbots and AI in Customer Service

Presently, bots have already delivered impressive results in customer service. Many businesses have rolled out chatbots to help them in distributing useful information and engaging the customers. For instance, Starbucks uses a system that allows customers to easily and quickly place orders using voice commands. The good chatbot will tell you the total price of your order plus when it will be ready.

Another noteworthy customer service company that uses bots is Lyft. Customers of the service can use online chat (Slack or Facebook) or AI voice chat (Amazon) to request for rides on the service. Lyft’s messenger bot offers the customer vital details. It shows the car model, a photo of the license plate, and the location of the driver.

Here are some practical ways you can use bots in your customer service business:

In the Automation of FAQs

Ask anyone if they read the FAQ section of a website, and you will probably get a hard and repetitive “no.” Rather than customers reading the questions, they would opt to email the company their queries. By leveraging chatbots and artificial intelligence, businesses can use appropriate documents to respond to any relevant questions.

As the Internal Help Desk

When an external customer service agent does not have an answer to a customer’s query, logically they would refer to the internal desk. And more often than not, this desk has to respond to the same questions over and over again. By using bots, internal customer service agents will not have to respond to common concerns.

In Offering Confident Responses

Interactive bots can ascribe a confidence score to their response. And if the score is below the threshold you had set, the bot will automatically contact a live agent and come back with a more satisfactory answer. In turn, the bot through Machine Learning can respond to similar queries in the future.

AI in Online Marketing and E-commerce

Some players in e-commerce have already started leveraging AI, and by the end of 2019, we can expect mainstream acceptance of the same. E-commerce companies such as Sephora, Asos, Sun’s Soccer, 1-800-Flowers, and Nitro Café are some of the companies that are already bringing in dollars in profit by deploying bots.

So, how can e-commerce stores and marketers use bots? For one, they can be used in customer support. Personalization is the key to every marketing strategy. And so far, bots have proven to be quite useful in providing personalized responses as compared to email or social media. People can express themselves much more freely when talking to chatbots. Therefore, to connect more with your customers, you can use a bot to interact with them and build or improve brand loyalty.

Another way e-commerce players are using artificial intelligence is in building interactive sales funnels. Marketers can use AI to group their customers and sell their products or services. A bot offers an opportunity to be dynamic and engaging. If a customer declines to try your service or product, the program can analyze the possible reasons to avoid the cases in the future.

You can also substitute emails with AI. By using a messenger chatbot, you significantly increase your click-through rates as compared to email. Most online marketers are already using chatbots to get information about visitors on their site as pop-up messages.

Some other benefits of using artificial intelligence in e-commerce include recouping abandoned carts, upselling after purchases, generating leads, providing useful AI algorithms for product recommendations, and boosting customer retention.

“83% of people who shop online need support, 56% prefer to get a text message, and 38% of people consider chatbots are even more useful. It is, therefore, good business to invest in a bot as an online entrepreneur,” – noted Andrew Ortiz, marketing specialist at Skillroads.

AI Online Chat in Tourism and Hospitality

Chatbots are already among the top technology trends in tourism and hospitality businesses. And in 2019, there are expected to be adopted on a wider scale. Bots are helping companies in this sector to reduce costs while also providing an excellent user experience. So far, bots have helped tourism and hospitality companies increase customer satisfaction. Some of the firms that have already witnessed the good results of using AI applications include Marriot, Snap Travel, KLM, Waylo, and Wynn.

You can use a bot in your business for different reasons. For instance, you can use it to engage customers before, throughout, and after the trip. Bots can send prospective and existing customers links to personalized content on hotels, destination sites, top restaurants, and so forth. Once a customer has booked a room, for example, a bot can come in to help them check in, request service, suggest activities, order meals from the restaurant, and more. Upon checking out, a bot can assist in collecting feedback and comments from customers.

Bots can also help in personalizing the customer experience. By doing this, they eliminate competition based on pricing. Customers often consider factors such as location and brand along with the price when choosing hotels. A bot can thus assist you to send out personalized packages to your customers and appeal to them. They help you put together all activities that interest the target audience and market the package to them specifically.

Chatbots and artificial intelligence can also be used in anticipating customers. By using predictive analysis, a hotel owner can identify future patterns and send out targeted campaigns to customers. For example, in 2014, Roof Inn used flight and weather data to predict the customers that were likely to face cancellations of their flights. In turn, they were able to send out campaigns on mobile devices to customers in locations that were likely to experience harsh weather. So what can we take from this? Bots can help in anticipating problems and addressing them way before they happen.

Artificial Intelligence in Financial Services and Banking

Financial tech companies such as Fintech are already causing waves in the industry by introducing bots. By 2020, it is expected that 85% of customers will use Fintech Chatbots to manage their bank transactions. Currently, some big banks are already using bots. These include Visa, MasterCard, Chase, American Express, Capital One, PayPal, Barclays, Ally Bank, and Bank of America.

So, how are financial companies using bots? First, Chatbots and AI are helping in smart messaging whereby they warn customers about dangers or other issues affecting their accounts. Second, they can also give you personalized tips on things you can do with your finances. Moreover, they can help you know how you are using your funds, how you are repaying your loans, and how you can save more money. And not to forget, bots are offering customers around-the-clock support and useful insight that improves customer experience.

It is important to note that, bots are expected to save financial institutions over $8 billion per year by 2022.

AI in Human Resource Management and Hiring

One of the big beneficiaries of AI has to be HR and recruiting. Bots have become integral in virtually all aspects of the employee lifecycle from sourcing, to screening, to interviewing, and finally to hire.

Employers are also using bots to boost customer engagement. These systems act as a bridge that connects employees to the existing job systems thus giving them better experience at the workplace. Maya is one of the companies that is automating all the stages of recruitment. SAP, Wade & Wendy, Loka, and SGT STAR are some other firms that are also using bots.

AI in Voice and IOT

Voice-powered assistants are increasingly becoming popular. Alexa, by Amazon, is one of the pioneer voice assistants and accounts for up to 70 percent of the market share. Come 2020; it is projected at least 128 million smart speakers will have been sold.

Final Thoughts on AI for Business

As an entrepreneur, AI is a tech trend to watch out for if you are keen on staying relevant, growing your business, and making a profit. Chatbots are cost-effective, time-saving, and most importantly give your customers a personal touch.

By Alice Berg

Alice Berg is a career advisor, who helps people to find their own way in life, gives career advice and guidance, helps young people to prepare for their careers. You can find Alice on Twitter and Medium.

Sourced from RUHANIRABIN

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3 Tips To Create A Mission That Will Drive Growth

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By  Kara Goldin

Last year, just over a third of small businesses grew their revenue. That gives you an idea of how hard it is to scale a startup. One mistake many entrepreneurs make is to think that growth is simply about increasing sales. True expansion demands more than just a great product or idea. You need a mission.

When a business has a clear and distinct purpose, it attracts the kind of employees who will drive growth. People who fit the culture of your company, share your ambitions and bring passion and enthusiasm to everything they do are 30% more likely to be high performers than those just there for the paycheck.

Having a mission also appeals to customers. Edelman’s Earned Brand 2018 report states that 64 percent of consumers take a brand’s principles into account when buying a product. Connecting with customers over shared values is a great way to build brand loyalty.

Finally, your purpose will guide your growth. Scaling is often where a business loses sight of what’s most important. A mission will keep you on the right path no matter how quickly growth comes.

It’s not always easy to know what your ultimate goal should be. Here are three tips for uncovering the mission that will drive growth at your business.

  1.   Make your customers central to your mission

Having worked in fashion publishing, Emily Weiss decided to start a blog where models, stylists and makeup artists would share their daily beauty routines. Soon her readers began sharing their own tips and advice with each other. Weiss realized that this community could shake up a beauty industry that typically relied on experts and brands to set the standards.

She founded Glossier, a beauty products company with a mission to democratize beauty. When creating a new moisturizer, the company asked customers for ideas and received more than 1000 responses. When marketing products, Glossier sends samples to its most engaged fans instead of the usual media outlets and social influencers. By making customers central to its mission, Glossier has grown from one woman writing a blog to a 150-person company that has raised more than $86m in funding.

  1.   Go back to your why

In Start With Why, writer Simon Sinek emphasizes the importance of purpose by stating “people don’t buy what you do, they buy why you do it”. Yet most startups inevitably focus on developing a product or service and finding customers. When they finally get time to outline a mission, they are so consumed with “what they do”, they’ve lost sight of their “why”.

As my business started to grow rapidly, I went back to the very beginning in order to articulate our purpose. I created our flavoured water drinks to solve a specific problem: I wanted to stop drinking sugary sodas but found water boring. Ultimately, I wanted to be healthier, so I took that “why” and expanded it to a mission of making people enjoy water again. This mission impacts who we hire, the new products we introduce and other decisions we make as we’ve become a multimillion-dollar business.

  1.   Don’t make your mission about what you’re selling

Not all businesses produce worthy or world-changing products or services. But that doesn’t mean you can’t have an inspiring mission. Warby Parker began life after business school graduate Neil Blumenthal wondered why people weren’t buying glasses online. Blumenthal thought about this because he was also involved in a non-profit organization that trained women in developing world to give eye tests. So, he and his co-founders made this social cause part of their company’s mission.

When you buy Warby Parker glasses, a pair is also donated to people in need. Blumenthal acknowledges that this isn’t the main reason why customers buy their products. But having a social conscious is core to the business as a whole: “To be customer first, you need to be employee first. And to be employee first, you need to be mission-driven.” It’s definitely working. Warby Parker was valued at $1.75 billion earlier this year.

Creating true brand believers

Whatever your businesses, chances are you’re not the only company out there offering that product or service. Even if you are doing something unique, others will try and replicate your success. To stand out you need to give people a reason to believe in your brand. Your purpose is that reason. And as it informs every person you hire, product you make and action you take, your mission will become the main driver of growth for your business.

By  Kara Goldin

I am the founder and CEO of San Francisco–based hint, which produces the leading flavoured water with no sweeteners and nothing artificial. I founded The Kara Network and recently launched my podcast Unstoppable to tell the stories of entrepreneurs and founders.

Kara Goldin is the founder and CEO of San Francisco–based hint, which produces the leading unsweetened flavoured water. Listen to her podcast and follow her on Twitter, @karagoldin.

Sourced from Forbes

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5 ways data and text analytics improve customer retention

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By  Agi Marx

Customer retention strategies fuelled by data ultimately influence how your team will approach customers — it’s proven to drive profit. In fact, “executive teams that make extensive use of customer data analytics across all business decisions see a 126% profit improvement over companies that don’t” (McKinsey, 2014).

This is no news. Among 334 executives surveyed by Bain, more than two-thirds said that their companies are investing in data and analytics. And the expectations are high. 40% expect to see “significantly positive” returns, with another 8% predicting “transformational” results (Bain & Co, 2017).

While the intention is there, according to Forrester, “only 15% of senior leaders actually use customer data consistently to inform business decisions” (“The B2B Marketers Guide to Benchmarking Customer Maturity”, Forrester, 2017). So, companies do realize the need for data but expect some sort of magic to happen in order to implement?

“Influencing customer loyalty […] doesn’t require magic, it requires data – usually data that you already have but aren’t using to full advantage. Regardless of industry, most organizations today generate mountains of data. In fact, many customers tell me that they have so much data that their biggest problem is how to manage all the data they have”, says Mike Flannagan, vice president, and general manager of Cisco.

5 Ways Data and Text Analytics Improve Customer Retention

1. Develop a data roadmap and stick to it

As many as 30% of the executives in the aforementioned Bain & Co study said that they lack a clear strategy for embedding data and analytics in their companies. McKinsey’s findings show that taking an integrative approach, meaning seeing analytics as a strategic driver of growth instead of using it in a silo or only as a part of IT, ultimately leads to achieving the desired result (McKinsey, 2014).

Successful companies do two things differently: First, they make use of the data they have. Second, they implement the organizational changes once they understand what the data tells them. So, you have the data – make sure you actually use it and enforce any changes needed in the business to make it happen quickly.

A good approach is to develop a data roadmap and stick to it. Steps that you take within the organization can be to:

  1. Ensure corporate KPIs are automated, scalable and repeatable.
  2. Gather key stakeholders and define the top 3 business problems you want to solve.
  3. Categorize the issues into data vs. systems issues (often you’ll find that the issue is not with “data” at all, but with how people use it or manage it).
  4. Prioritization of tasks is required along with assessing the technical feasibility of your plan.
  5. To stay on track, reassess progress every 3 months.
  6. The human factor – ensure behavioral change

Another key factor is hiring senior executives who take a hands-on approach to customer analytics. Not only do they need to understand the importance of analytics but also have the skills to analyze it themselves, so use this as a benchmark when hiring.

Although 70% of companies have data strategies in place, many will fail to deliver what’s needed due to one factor alone: people. You may have the most advanced tools and excellent data scientists; however, all efforts fail without the correct behavioral changes needed internally to ultimately take action (Bain & Co 2017).

Employees may not be committed to using data analytics, internal teams may not be communicating with each other, or the data solutions adopted aren’t user-friendly. Behavioral change, continuous monitoring of results, along with a “one-team approach” is needed to ensure that advanced analytics within an organization can survive and prosper (Bain & Co, 2017). No surprises here, behavior change being the hardest part of any performance improvement plan and why as many as 38% change efforts fail (Bain & Co, 2016).

2. Only focus on high-quality leads

Customers are less likely to churn if they are similar to your primary target customers. If you have access to data about both your customers and a list of potential customers, this is a great opportunity to focus on only those who are less likely to churn.

How? By applying algorithms comparing the features and characteristics of your customers to those of your potential customers. Those that have similar characteristics (FTE size, annual spend, job title, type of industry) to your existing customers are probably those most likely to want your product, to find it valuable and therefore stick around. Your segmentation now becomes crucial. Each customer segment provides you with distinct features that help easily identify your next customers.

For example, tools like HubSpot provide this type of information in an integrated way, where you can see characteristics and patterns easily.

3. Use machine learning methods to create predictive models

Companies analyze data using different types of analytics, including predictive analytics, which is used to look at the relationships among different metrics.

To create solid customer retention strategies, we can use predictive analytics to make predictions about the future, by looking at historical data, to learn what customers may like or dislike.

Often, you might be overwhelmed by the number of variables you have to manage and analyze all at once. Although you may have a highly skilled data analyst at hand, it’s still time-consuming and labor-intensive to manually and quickly sift through the sheer volume of data to find the optimal predictive model.

To create the best predictive models of retention, rely on the power of machine learning to quickly and accurately uncover the underlying reasons why customers are churning or why they’re loyal to your brand.

Machine learning uses math, statistics and probability to find connections among variables that help optimize important outcomes such as retention. These models are then applied to new customer data to make predictions.

Machine learning algorithms are iterative and learn on a continual basis. The more data they ingest, the better they get. Compared to human performance, they can deliver insights quickly thanks to the processing capability of today.

For example, you can use analytics to identify which up-sell or cross-sell products will be the most relevant based on your customer’s past purchase or browsing history.

Often, companies don’t have employees with high-level analytics (data science) skills. Third party providers can provide a solution that automates data integration and analysis.

4. Get data-driven insights with text analytics

To get deep, data-driven insights, don’t forget to analyze your free-text responses to your open-ended survey questions. If you don’t you may well miss them!

You can do this with text analytics solutions. With a text analytics tool that uses sentiment analysis, it’s easy to spot customer pain points.

And, if you collect lots of data, make sure you actually use it. One study found that only 15% of senior leaders actually use customer data consistently to inform business decisions (Harvard Business Review).

At Thematic, we have developed an AI algorithm that automates analyzing free-text feedback in surveys using machine learning and natural language processing, and in essence, simplified the way businesses are getting insight from their customer data.

5. Segment to focus on retaining the right customers

Using data analytics to segment people into different groups means you can identify how each segment engages with your brand and product. This then allows you to look at each subgroup and draw insights, followed by adopting different communication and servicing strategies to increase retention of your most wanted customers.

Analyze data such as your customer demographics, lifestyle, products purchased by each category and type of customer, the frequency of purchase and purchase value. In this way, you’ll discover which type of customers are driving the most revenue. Some cost too much to deliver revenue, so you’ll know if you want to focus your efforts on.

Understanding the difference between these types of customers, can in some cases make or break a business, especially if you’re just starting out. Knowing customer value is crucial to be able to make critical decisions. You can segment by historical value, lifetime value, value over the next year or the average customer value by segment. Using the right segmentation, you’ll then create highly targeted product recommendation offers. Segment your customers to offer relevant discounts for different channels (in-store, online, mobile). Mix it up a bit, every customer doesn’t have to receive the same offer.

Another useful way to use segmentation is to monitor the time-sensitivity and seasonality of your promotional codes. By monitoring sales data, you can see whether these codes are redeemed more often in the morning or afternoons or perhaps straight after a sales communication. The more you know about what a demographic responds to, the more you can focus on taking the right actions.

Top 3 Tips for Analysis

Gather multiple data points to be able to make relevant recommendations.

Be pragmatic and avoid making assumptions from solely one piece of data. Because someone living in California buys winter boots doesn’t mean they want to be bombarded with similar product suggestions. Maybe they bought them for their sister who lives in Chicago!

Leverage social proof where you can.

If your customers don’t respond to certain products, maybe all they need is a little reminder that others similar to them are using them and are happy with them. Pull in positive testimonials from surveys and social media comments to your marketing communications and website.

Remember: it’s the ability to swiftly translate insightful data into concrete action that counts.

It’s a fact: better data means better results. If you don’t have good data now, you can test your way to better data. Just by improving your internal data collection, you can often arrive at better data. In other cases, you might have to purchase better data. Good data is not static, it’s a continual process of observing, acting and learning.

Finally, the challenge of the vast data volume that large businesses have, is also the opportunity. Bringing together structured and unstructured historical data across organizational silos, and combining it with key data about ongoing customer interaction provides a compelling opportunity to influence customer experience in real time.

This article was published here first.

By  Agi Marx

Sourced from Digital Doughnut

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Data Analytics Most Instrumental in Enhancing Customer Experience and Lowering Risk for Organizations

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Sourced from BW CI World

Innovating new business models and maximizing revenue and profits are the next set of priorities for data analytics

Infosys published a global research on data analytics from the Infosys Knowledge Institute. The survey titled, ‘Endless possibilities with data: Navigate from now to your next’, reveals that a majority of organizations are deploying analytics to enhance customer experiences and mitigate risk.

This research tries to understand how data analytics is becoming core to driving digital transformation for enterprises and makes an assessment of enterprise expectations in a world of endless possibilities with data. It also explores a range of challenges, opportunities, and the role of new technologies in the analytics world.

Highlights of the survey
* 31 percent of respondents identified the use of analytics with experience enhancement. This includes using intelligence generated by listening to internal and external stakeholders to drive extreme personalization and high quality customer service

* 28 percent respondents were interested in leveraging analytics for risk mitigation – predicting risk to enable better decision making, and detecting anomalies that could disrupt business effectiveness.

* Developing new business models by unearthing the latent needs of customers and offering innovative products and services was seen as the primary analytics requirement of 23 percent of respondents.

* Revenue and profit maximization through increasing channel effectiveness, and thereby, enhancing profitability across processes, channels and stakeholder ecosystems was the analytics priority for the remaining 18 percent.

* The majority of respondents in the U.S. (32 percent) and Europe (34 percent) stated they would like to use analytics for experience enhancement whereas in ANZ about 31 percent respondents consider it for risk mitigation.

Functions across organization are benefiting from the possibilities of data. Finance and accounting was found to use analytics the most at 32 percent, followed by marketing and operations at 20 percent and 17 percent, respectively. In terms of the emerging technologies, Artificial intelligence was perceived to deliver increased outcomes when combined with analytics at 37 percent followed by IoT and Cloud Technologies at 19 percent and 16 percent, respectively.

The survey found that enterprises in every industry encountered several challenges that prevented them from implementing their analytics initiatives fully. The biggest challenges stemmed from a lack of expertise in integrating multiple datasets (44 percent of respondents) and failure of understanding in deploying the right analysis techniques (43 percent).

This is where enterprises are looking up to their partners to help industrialize their analytics capabilities by creating an analytics strategy, build an operational framework, and define a process for executing and governing analytics initiatives.

Sourced from BW CI World

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In-Feed Native Ads: Measuring Native Advertising

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By Julien Verdier

As published by our co-founder, “Native advertising is a form of paid media where the advertisement is relevant to the consumer experience, integrated into the surrounding content and is not disruptive.” The advertisement is in-feed and is relevant to the content on the page. As CEO of a native advertising platform, I’m seeing the native advertising industry experience phenomenal growth, especially on mobile.

When introducing native to your marketing campaign, you need a clear view of what you want the results to be. In order to succeed with your in-feed native ads, you first need to define what success actually looks like. What is the metric you are going to use to determine whether or not your native advertising is a success? For the majority of in-feed native advertising campaigns, key performance indicators (KPIs) typically fall into one or more of the below:

CTR: Click-through rates (CTRs) are often used as a KPI, particularly when it comes to programmatic native advertising.

Visits: Rightly or wrongly for many advertisers, the No. 1 criteria for success when they run native advertising campaigns is: How many visits did it bring to my site?

Dwell Time And Bounce Rate: These two KPIs often go hand in hand with visits as a measure of success. Dwell time is the measure of how long a visitor spends on a specific page, so it can be used — in a slightly crude fashion — as an indicator of whether someone read and enjoyed the content on the page.

Bounce rate, which is a key search metric, is the indication of what the user did after landing on the page. Did they click back or close the window, or was their interest piqued enough by this page to move along to other pages on the site? Both are metrics used to understand the stickiness of content and websites, and to tell if visitors enjoy these pages.

Engagement: This is a similar KPI to dwell time, but the process of measurement is very different. While dwell time is typically measured through the advertisers’ website, usually via Google Analytics, engagement is a metric that is usually measured via a publisher, native technology platform or another third-party ad-tracking tool.

What does it mean? It is a measure of how long someone engaged with your content. This could be how long, on average, someone spent reading your branded content published on a site. Or it could be the average length someone spent watching your brand video.

Shares And Likes: For many advertisers, native advertising is a tool to be used to generate shares of their content and likes for their pages. This is particularly true, though not exclusively, with social media advertising. For many advertisers using social media advertising, they are looking for as many shares of their content as possible — shares that hopefully translate into lots of likes for their social media profiles, and more visitors to their site. But, ultimately, shares equal extended reach for your brand’s marketing messages and increase the available pool of relevant customers you can engage with at any point in the future.

Sales And Leads: While soft metrics, such as engagement and visits, are very popular measures of success, native advertising is increasingly being used as a pure direct response marketing channel. For these advertisers, success is easy to quantify: Did I create any sales leads? Did I manage to generate any sales as a result of this native advertising?

Sophisticated advertisers increasingly use native advertising in conjunction with other forms of digital advertising for strong sales results. When combined with data, retargeting, cookies and attribution modeling, native advertising is a growing part of the modern sales lead marketing mix.

Challenges Of Measuring In-Feed Native Advertising

The onset of native and content-based advertising solutions has presented the industry with a complex challenge: How do we establish meaningful and consistent measures that underpin the digital trading environment and allow the evaluation of campaign effectiveness?

Using standard metrics will give you the numbers you want — the impressions, reach, clicks, etc. And through this, you will be able to show whether a native ad was successful compared to other advertising formats. However, I believe these serve as a reporting comparison but do not give full insight into the value of native advertising. How you measure a native ad should differ according to the campaign and its objectives and be tailored toward this.

In June 2016, the IAB U.K.’s Content and Native Council published its Content and Native Measurement Green Paper, in which our company weighed in, along with 15 other companies. If the paper has a conclusion, it’s that there is much work to be done to be open and transparent with all data points for consistent, algorithmic measures and techniques to be developed.

The point on which everyone agreed is that current digital trading metrics were only a part of the solution and that, as with traditional media, there has to be an investment in understanding how people behave with content-based and native advertising before establishing algorithms that measure those behaviors.

Feature Image Credit: Pexels

By Julien Verdier

CEO of ADYOULIKE, AI-Powered Native Advertising platform.

Sourced from Forbes

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YouTube Officially Rolls Out YouTube Stories

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Welcome to this week’s edition of the Social Media Marketing Talk Show, a news show for marketers who want to stay on the leading edge of social media.

On this week’s Social Media Marketing Talk Show, we explore YouTube’s rollout of YouTube Stories to more creators. Our special guest is Steve Dotto.

Watch the Social Media Marketing Talk Show

If you’re new to the show, click on the green “Watch replay” button below and sign in or register to watch our latest episode from Friday, December 7, 2018. You can also listen to the show as an audio podcast, found on iTunes/Apple Podcast, Android, Google Play, Stitcher, and RSS.

Click HERE to read the remainder of the article.

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Sourced from Social Media Examiner

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Meeting the intelligent data management needs of 2019

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By Mark Bowen

Dave Russell, Vice President for Product Strategy at Veeam, outlines five intelligent data management needs CIOs need to know about in 2019.

The world of today has changed drastically due to data. Every process, whether an external client interaction or internal employee task, leaves a trail of data. Human and machine generated data is growing 10 times faster than traditional business data, and machine data is growing at 50 times that of traditional business data.

With the way we consume and interact with data changing daily, the number of innovations to enhance business agility and operational efficiency are also plentiful. In this environment, it is vital for enterprises to understand the demand for Intelligent Data Management in order to stay one step ahead and deliver enhanced services to their customers.

I’ve highlighted five hot trends in 2019 decision-makers need to know – keeping the Europe, Middle East and Africa (EMEA) market in mind, here are my views:

  1. Multi-Cloud usage and exploitation will rise

With companies operating across borders and the reliance on technology growing more prominent than ever, an expansion in multi-cloud usage is almost inevitable. IDC estimates that customers will spend US$554 billion on cloud computing and related services in 2021, more than double the level of 2016.

On-premises data and applications will not become obsolete, but that the deployment models for your data will expand with an increasing mix of on-prem, SaaS, IaaS, managed clouds and private clouds.

Over time, we expect more of the workload to shift off-premises, but this transition will take place over years, and we believe that it is important to be ready to meet this new reality today.

  1. Flash memory supply shortages, and prices, will improve in 2019

According to a report by Gartner in October this year, flash memory supply is expected to revert to a modest shortage in mid-2019, with prices expected to stabilise largely due to the ramping of Chinese memory production.

Greater supply and improved pricing will result in greater use of flash deployment in the operational recovery tier, which typically hosts the most recent 14 days of backup and replica data. We see this greater flash capacity leading to broader usage of instant mounting of backed up machine images (or copy data management).

Systems that offer copy data management capability will be able to deliver value beyond availability, along with better business outcomes. Example use cases for leveraging backup and replica data include DevOps, DevSecOps and DevTest, patch testing, analytics and reporting.

  1. Predictive analytics will become mainstream and ubiquitous

The predictive analytics market is forecast to reach $12.41 billion by 2022, marking a 272% increase from 2017, at a CAGR of 22.1%.

Predictive analytics based on telemetry data, essentially Machine Learning (ML) driven guidance and recommendations is one of the categories that is most likely to become mainstream and ubiquitous.

Machine Learning predictions are not new, but we will begin to see them utilising signatures and fingerprints, containing best practice configurations and policies, to allow the business to get more value out of the infrastructure that you have deployed and are responsible for.

Predictive analytics, or diagnostics, will assist us in ensuring continuous operations, while reducing the administrative burden of keeping systems optimised. This capability becomes vitally important as IT organisations are required to manage an increasingly diverse environment, with more data, and with more stringent service level objectives.

As predictive analytics become more mainstream, SLAs and SLOs are rising and businesses’ SLEs, Service Level Expectations, are even higher. This means that we need more assistance, more intelligence in order to deliver on what the business expects from us.

  1. The ‘versatalist’ (or generalist) role will increasingly become the new operating model for the majority of IT organisations.

While the first two trends were technology-focused, the future of digital is still analogue: it’s people. Talent shortages combined with new, collapsing on-premises infrastructure and public cloud + SaaS, are leading to broader technicians with background in a wide variety of disciplines, and increasingly a greater business awareness as well.

Standardisation, orchestration and automation are contributing factors that will accelerate this, as more capable systems allow for administrators to take a more horizontal view rather than a deep specialisation.

Specialisation will of course remain important but as IT becomes more and more fundamental to business outcomes, it stands to reason that IT talent will likewise need to understand the wider business and add value across many IT domains.

Yet, while we see these trends challenging the status quo next year, some things will not change. There are always constants in the world, and we see two major factors that will remain top-of-mind for companies everywhere….

  1. Frustration with legacy backup approaches and solutions

The top three vendors in the market continue to lose market share in 2019. In fact, the largest provider in the market has been losing share for 10 years. Companies are moving away from legacy providers and embracing more agile, dynamic, disruptive vendors, such as Veeam, to offer the capabilities that are needed to thrive in the data-driven age.

  1. The pain points of the Three Cs: Cost, complexity and capability 

These Three Cs continue to be why people in data centres are unhappy with solutions from other vendors. Broadly speaking, these are excessive costs, unnecessary complexity and a lack of capability, which manifests as speed of backup, speed of restoration or instant mounting to a virtual machine image. These three major criteria will continue to dominate the reasons why organisations augment or fully replace their backup solution.

  1. The arrival of the first 5G networks will create new opportunities for resellers and CSPs to help collect, manage, store and process the higher volumes of data

In early 2019 we will witness the first 5G-enabled handsets hitting the market at CES in the US and MWC in Barcelona. I believe 5G will likely be most quickly adopted by businesses for Machine-to-Machine communication and Internet of Things (IoT) technology. Consumer mobile network speeds have reached a point where they are probably as fast as most of us need with 4G.

2019 will be more about the technology becoming fully standardised and tested, and future-proofing devices to ensure they can work with the technology when it becomes more widely available, and EMEA becomes a truly Gigabit Society.

For resellers and cloud service providers, excitement will centre on the arrival of new revenue opportunities leveraging 5G or infrastructure to support it. Processing these higher volumes of data in real-time, at a faster speed, new hardware and device requirements, and new applications for managing data will all present opportunities and will help facilitate conversations around edge computing.

Feature Image: Dave Russell, Vice President for Product Strategy at Veeam

By Mark Bowen

Sourced from INTELLIGENT CIO

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7 Content Marketing Tasks to Automate Right Now

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By Aaron Agius

Rapid advances in AI technologies mean marketing automation is no longer optional. It’s a mainstay of modern marketing.

Not all content marketing tasks can or should be automated. No matter how far AI advances go, software will never replace a human for crafting an insightful and meaningful blog post.

But as you go through your daily content tasks, it’s worth asking, “Can this be automated?” Chances are, many of them can.

Let me help you choose the areas to automate to plan your approach effectively.

Proofreading: Grammarly

Cost: Free browser extension or paid premium version

You could write a great piece of content, but your readers won’t trust it (and many won’t even read it) if it’s full of spelling and grammar errors.

It takes a lot of time to go through a draft with a fine-toothed comb to find and correct every mistake.

Tools like Grammarly can automate proofreading in a more comprehensive way than the usual spelling and grammar features found in Microsoft Word and Google Docs.

The free Google Chrome extension offers basic spelling and grammar corrections in almost every place you write content across the web – web-based emails, social media updates, Google Docs, etc.

The paid version ($11.66 per month) picks up more advanced errors and suggests enhanced vocabulary. It also can identify plagiarism to help make sure you don’t duplicate content.

Email marketing

According to a recent survey from Econsultancy, email is the most effective channel. It helps you garner and follow up on leads and helps prospects through the sales and after-sales processes.

But data shows that companies are spending far too much time producing emails. According to The Litmus 2017 State of Email Report, 68% of companies take at least one week to produce one email. With most companies reporting having one to five emails in production at any given time, that means a lot of time is spent just on email. Yet there’s an abundance of automation software to choose from, including BuzzBuilder Pro and Mailchimp.

List building: BuzzBuilder Pro

Cost: $250-plus a month

Taking into account the testing of content and subject lines, cold lead generation can take months to execute.

BuzzBuilder Pro helps automate and speed up list building. It helps craft personalized cold emails and integrates with your LinkedIn account to send follow-up emails. Other features include a web form builder, social media marketing, and hot lead alerts.

Automated emails: Mailchimp

Cost: Free and paid versions (starting at $10 per month)

From a simple “Thank you for signing up for our newsletter” to “You have items in your shopping cart,” emails offer you an opportunity to keep your customers informed and engaged.

Mailchimp is up there with the best of the automated email software. It lets you store thousands of contacts at a time, segment and A/B test them, and create campaigns that you can save and reuse later. It also lets you schedule your email send times to get the optimal open and click-through rates.

Its automation feature lets you set up complex workflows based on triggers so your customers receive the right kind of email at the right time.

BONUS TOOL: GetResponse (pricing starts at $15 per month) covers much of what Mailchimp does (email workflow automation, triggered events and emails, and lead nurturing). But it’s expected to introduce a CRM feature to allow brands to measure their relationship with their customers in the same place they automate their email workflow.

Social media promotion: Zapier

Cost: Free trial; tiered pricing starting at $20 per month)

Promoting your content via social media is another time-consuming task, especially if you manage several platforms at a time, from pinning to Pinterest, to tweeting via Twitter, to uploading to Facebook. And that doesn’t include the time to “like” and share other content.

Platforms like Buffer are great for bulk-uploading your content in advance and scheduling it to send out to your various social accounts. Integrate it with Zapier and this process can be automated.

Once you set up your Zapier account, you link it to your social media profiles. You also need to set up your RSS feed. If you need help with RSS, read this guide.

Click on the “explore” tab to set up your cause-and-effect triggers. In the following example, when a new item is published to my blog, it’s automatically posted to my Facebook page.

Set up a few cause-and-effect triggers so each time you publish a blog post it automatically gets promoted on your social media.

Workflow automation: IFTTT

Cost: Free

IFTTT (If This Then That) is a go-to for any marketer wanting to automate content workflow. Since its 2010 launch, it’s been free. The automation possibilities are almost endless.l

IFTTT lets you connect your online “services” (e.g., social media accounts, WordPress blog, Gmail account, Google Calendar, and even other external blog RSS feeds) and set up condition statements (applets) that trigger an automation.

For example, you can set up an applet so that every time you post to Facebook, it immediately shares it on your Instagram account. Or, if you want to regularly share industry or topic-related news from The New York Times, your applet could automate posting news from a category (e.g., world news) to your Twitter feed:

Other IFTTT recipes to consider:

  • Sync your WordPress site with social media so when you post a new blog article it immediately shares to your social profiles.
  • Sync your Instagram and Pinterest accounts so every time you post a photo on Instagram, it is shared to one of your Pinterest boards.
  • Sync your YouTube account to social media so every time you upload a new video, it posts to your social profiles.

Monitoring and analysis: Google Analytics

Cost: Free

Google Analytics lets you set up custom reports to automatically send updates on the data you want to focus on. It can be helpful to identify what content is getting the most engagement and pinpoint content areas that drive the most traffic and conversions.

Time to do more

Content marketing is time-consuming work that requires daily input if it’s to bring any kind of ROI. And time, as we know, is money.

But, thanks to advances in big-data technologies and AI, automation is more cost-effective and user-friendly than ever. If you want to streamline your content ideation, creation, curation, and promotion, then it’s time to automate.

And better still, automate your analytics so you’re receiving regular and accurate insights into how your content is performing.

With these tasks automated, you’ll be freed to do more strategic work. Knowing that a lot of your content marketing is ticking on by itself will give you the breathing space to think about new and creative directions in which to take your content marketing.

What tasks do you automate? What tools have you found helpful? Please share in the comments.

Please note: All tools included in our blog posts are suggested by authors, not the CMI editorial team. No one post can provide all relevant tools in the space. Feel free to include additional tools in the comments (from your company or ones that you have used).

Automate your education in content marketing. Subscribe for the free weekday newsletter from the Content Marketing Institute. 

Cover image by Joseph Kalinowski/Content Marketing Institute

By Aaron Agius

Aaron Agius is an experienced search, content and social marketer. He has worked with some of the world’s largest and most recognized brands to build their online presence. See more from Aaron at Louder Online.

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Sourced from Content Marketing Institute

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How to Build a Facebook Ad Funnel

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By Juupiner

Do you want more conversions from your Facebook ads?

Wondering how funnels can help?

To explore how you can build Facebook ad funnels that improve conversions, I interview Susan Wenograd.

More About This Show

The Social Media Marketing podcast is an on-demand talk radio show from Social Media Examiner. It’s designed to help busy marketers, business owners, and creators discover what works with social media marketing.

In this episode, I interview Susan Wenograd, a Facebook ads expert who specializes in Facebook ad funnels. She’s also a consultant and regular speaker on Facebook ads.

Sue explains how video-based funnels create micro-conversions.

You’ll discover how to nurture prospects using a Facebook ad funnel.

Facebook Funnels

Susan’s Story

Susan got her start in ecommerce in the mid-2000s, when she worked for Circuit City. Back then, her focus was email marketing and paid search. After she moved to another job, she learned about Facebook advertising. At the time, Facebook ads were easier to learn because Facebook had half of the advertising features it does now.

Running Facebook ads, Susan was able to experiment and get to know the platform. She loved that these ads took her back to the marketing 101 stuff she enjoys: branding, content, the language you use, and so on. Facebook ads allowed her to use a little more creativity than paid search did.

Click HERE to read the remainder of the article.

By Juupiner

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