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4 Technologies to Scale your Business with Limited Budget

Different founders define the word “scaling” differently. Therefore, it is necessary to identify which definition to zero in on. If scaling means using your existing data to close deals more predictably, then this article’s for you.

An ideal way to scale your business is by leveraging technology. In 2020, we expect to see a surge of 50% in small business tech spending due to increase in affordability of today’s cloud-based services and mobile devices.

Small businesses are confident about accessing new markets and targeting new customers at relatively lower costs using digital tools.

According to a Deloitte research, with the help of technology, small businesses, with less than 250 employees can:

  • Create 3X more jobs than the previous year
  • Earn 2X as much revenue per employee
  • Experience 4X as growth over the past year

Despite the potential gains and openness, 80% of small businesses are failing to take the full advantage of technology. Adding to that, here are four technologies that can scale your small business efficiently on a limited budget:

  1. Using Artificial Intelligence for higher control and visibility of your sales performance

87% of small businesses said they were using or considering to use AI to forecast sales. [Statista]

Statista

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Many small businesses tend to prefer the human touch in sales as it involves direct interactions with clients. Blend it with automation and machine learning to make your sales team more effective and productive.

For instance, there are virtual sales assistants powered by artificial intelligence that predicts the number of customers who would churn as well as algorithms that tell you the kind of customers who would churn. For such segments, you could create specific reminders or promotions, to keep them engaged.

Datoin is an automated AI-based platform that helps small businesses improve the performance of their sales teams. Datoin helps businesses get visibility of the following metrics:

  • Churn rate for the month
  • The customers likely to churn
  • Predicted demand for products
  • Price predictions for products that might fetch higher transactions
  • Forecasting daily sales

Datoin is designed to be used by business owners. For businesses who do not have data scientists, Datoin is a plug and play platform where you can enter the data. The platform starts analysing this data and shares the insights.

Click here to sign-up for using AI for free, with Datoin. https://app.datoin.com/signup

Some tools compile data from previously won and lost deals and also gather data from sales calls, meetings, and emails to determine what factors are likelier to lead to a successful sale. All of these can help your sales team close deals more predictably and boost their confidence by providing them with data-backed inputs.

What does AI Mean for an eCommerce Business?

  1. Let technology streamline your onboarding process.

36% of HR professionals agree that lack of technology is why they are unable to organize and automate onboarding programs. [Kronos]

As your business grows, you will be hiring new people more often. Completing all the paperwork and collating all the documents for those recruits can be a tedious task, both for your small business and for the people joining.

You can thus make things easier for your human resources team by using technology to streamline onboarding. For instance, there are several apps such as Gusto and HROnboard that allow new employees to finish all their paperwork and get connected online to the rest of the team even before they join work. They give the recruits an in-depth view of the company’s culture and vision, set up an agenda for their first day, and help them set work goals for the initial 90 days.

Many apps can also sync with other HR and communication software solutions, such as by automatically adding new employees to Slack groups, Gmail accounts, or messaging groups. With technology, you can make more time for interactions with the team – which is the essence of any onboarding program.

5 Most Common Customer Retention Strategies used by Small Businesses

  1. Use machine learning to automate new projects and daily tasks.

97% of companies agree that project management is critical to business performance. However, 44% of project managers use no software to manage tasks. [PwC]

While your existing process frameworks may be robust enough to handle day-to-day requirements, starting on a blank slate with each new project is time-consuming. This is where machine learning plays a significant role.

By training itself based on historical performance data and automating essential design decisions based on stipulated parameters, machine learning can eliminate repeated work and thus cut project-design costs for your small business.

The technology can also handle repetitive day-to-day tasks such as billing and invoicing, managing social media, handling customer support communications, and more.

That takes off a significant portion of performing the mundane tasks from your employees’ shoulders, to allow them to focus better on high-end tasks that call for more creativity and critical thinking. This leads to overall productivity enhancement for your small business.

Artificial Intelligence in eCommerce: 4 Tasks worth Automating

  1. Use chatbots to respond quickly to customer service queries

80% of businesses are expected to have chatbot automation by 2020. [Oracle]

When you are just starting, a small team of customer service executives are capable enough to handle all the queries that come through. As you expand your business, customers would want their issues to be solved immediately, around the clock.

That is where chatbots play a crucial role. They can efficiently handle a large variety of customer queries and complaints while maintaining a conversational tone and redirecting to a support executive when it fails to grasp the contact or when asked specifically by the customer.

Chatbot use cases

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They can also engage with the customers by redirecting them to specific pages, answering the frequently asked questions, requesting product reviews, or providing short questionnaires for feedback.

Particularly, if you are planning to reach a global audience, a chatbot can engage website visitors from around the world and in different time zones, which an in-house team would be unable to do all the time.

6 Applications of Artificial Intelligence for Small Businesses on a Budget

Summing it up

The modernization of technology has supported small businesses in many ways, and their use will only increase in the coming years.

There’s no denying that artificial intelligence is going to be a fundamental element in the future, with 72% of industry leaders calling it a “business advantage.”

Small businesses are leveraging in their day-to-day functioning.

Start using Artificial Intelligence for free, with Datoin. Leverage the power of machine learning, for your business. Sign-up for a trial today!

Importance of Sentimental Analytics for Small Businesses: A Quick Guide

Sentiment analytics has proven to be a useful tool for marketers; it helps them identify if their business is engaging its target audience or not. Let us understand how.

While it is always a challenge to start a company from scratch, technology has made it easier for budding entrepreneurs to keep track of how their business is performing. A technology that has transformed the way large-scale enterprises, startups, and more importantly, SMB marketers’ function, is sentiment analytics.

In simple words, sentiment analytics is a form of data mining that uses advanced technologies such as machine learning, natural language processing (NLP), and computational linguistics to extract and identify subjective information on websites, social media, and other similar forums.

Sentiment analysis for small business

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The tools used for sentiment analysis scan the content and identify and mine data points that present emotion as either positive, neutral, or negative. The data could be related to comments on social media, customer reviews on your website or online forums, or mere engagement with your brand on mobile.

Although the machine learning algorithms in sentiment analytics are highly capable of identifying emotions by reading and extracting data, sarcastic comments or irony is difficult to interpret for these models.

Even so, sentiment analytics has proven to be a useful tool for marketers to help grow their business. The main goal being, to understand how your business is engaging with its target market.  

sentiment analysis engagment outcome for small business

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Once that is in place, you can focus on other aspects of digital marketing such as monitoring customer engagement, responding to queries or reviews, tracking social mentions, and so on. Now, let us take social media as an example and understand how sentiment analysis makes a difference in this tactic:

Social media engagement is an inescapable area for all types of businesses today. And your small business is no exception. Social media increases your brand’s visibility, attracts more customers and drives higher profits. And sentiment analytics factors into that massively.

The power of social media marketing for small business.

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Social media automatically opens your business to a broader customer base and target markets because it covers all your demographics. Not just that, it also allows for two-way communication between the brand and its customers on a more personal level. Additionally, business owners get to address customer queries quickly. Today, customer service is more about the speed of response, and social media allows you to do just that.

An essential use of sentiment analytics in social media is to gauge how your customers are responding to your posts, shares, links, and so on. By using this information, you can create more customized social media campaigns that will, in turn, get you a better business.

The power of sentiment analysis in social media

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Simply knowing the sentiment doesn’t do much for you in terms of marketing. What you need are specifics and details. Metrics and key performance indicators (KPIs) are values by which you can identify and measure the performance of your business or website. Here are some of the critical metrics to keep track of:

1. Volume

Because social media trends are fleeting, it is vital to measure how much engagement your brand is receiving. Volume does that for you. It tells you how many people are talking about your business or your posts on social media. Although not a vital metric, it throws light on the general pulse that consumers feel about you.

2. Reach

This metric represents the social media reach of your business. In other words, it measures the reach of your posts. It denotes the number of people your posts are reaching on social media versus the number of people you can potentially reach out to.

3. Engagement

Another vital metric to measure how much buzz your business generates on social media is engagement. This could be in the form of likes, comments, and shares. Every marketer knows that social media engagement can do wonders for the business.

Engagement could be the turning point because social media posts can go viral in a few hours or not get noticed for months. High positive engagement is a sign that there will be more sales for you.

The reach is high in such a scenario, and the conversation about your business is positive – leading to higher conversions.

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4. Influence

Influencer marketing is a great way to get other individuals to promote and spread awareness of your business. This is not the same thing as the number of followers because that alone is not sufficient to determine how much engagement your business is getting.

That’s why there are various tools such as TwentyFeet and Crowdbooster that help you calculate an influencer score to give you a more detailed idea.

Influencer marketing

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5. Competition

Perhaps, one of the most underrated metrics is the comparison of your business performance as compared to that of your competitors.

Understanding what works for them versus what works for you gives you a clear picture of what is going well for you and which areas need to be improved upon. Also, you can even understand what the things you should not do; learn from the competitors’ mistakes.

Over to you

In a day and age, where an increasing number of customers interact with brands online, it is necessary to know how they feel about your business. Sentiment analytics, if leveraged properly, can give great actionable insights into how well or poorly your business is performing.

Adding to that, start implementing AI and ML technologies for free, with Datoin, and see the difference they create. Sign-up for a trial today!

How Can Traditional Businesses Leverage Artificial Intelligence for Sales?

Traditional organizations are tapping into data, algorithms and digital networks to compete with their rivals. Artificial intelligence has a deep impact on sales, operations and strategy.

There are three critical elements of business growth – save time, save money, and of course, increase sales. The majority of small businesses, irrespective of size or industry, invariably focus on the last element, i.e., boosting sales rapidly.

In response, their sales teams end up resorting to unsystematic tactics that not only waste time and resources but doesn’t lead to any long-term customer acquisition wins. That happens mainly because of their increased focus on urgent but ad-hoc tasks.

Impact of artificial intelligence on sales

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The good news is that Artificial Intelligence (AI) has immense potential to take the sales function of any small business to greater heights. Gartner predicts that by this 2020, 30% of businesses will deploy AI to augment their primary sales processes.

How Can Traditional Businesses Leverage Artificial Intelligence for Sales?

Adding to that thought, let us take a look at six ways in which traditional businesses can benefit immensely from AI technologies when it comes to sales:

1. AI can provide valuable assistance to sales teams.

Machine learning algorithms can be used to analyze large volumes of historical and real-time data, identify buying patterns, and glean actionable insights from that analysis. The sales team can then design and draft customized campaigns for upselling and cross-selling their offerings to a specific target audience.

The technology can take into consideration different types of factors – including demographics, technographic, and firmographic data points, which helps uncover unexplored areas of the business and make necessary changes.

For example, Datoin, an automated machine learning plug and play platform that any business can use, to gain insights from their data. You can use Datoin to gather data about:

  • The customer churn rate for the month
  • The customers likely to churn
  • Predict the demand for merchandise
  • Price predictions on the items that could fetch higher transactions
  • Forecasting daily and monthly sales

Click here to sign-up for using AI and Ml for free, with Datoin – https://app.datoin.com/signup.

2. AI facilitates lead qualifying.

While traditional lead acquisition methods are still in use today, artificial intelligence has made it possible for businesses to connect with potential customers on a more personal level through social media, emails, mobile apps, online forums, and other digital channels.

AI tools are capable of analyzing big data and identifying prospective leads for a business. Platforms such as Microsoft Azure Machine Learning and Google Cloud Prediction API are effective in enabling this.

Besides, AI-powered analytics tools, such as Google Analytics, are useful when there is a need to understand and strategize the lead qualifying and converting strategies.

A Quick Guide to Forecasting Sales Using Artificial Intelligence

3. AI can process a lot of data without human intervention.

Although sales are an intuitive profession that would require the sales team to understand and evaluate their target customers, the function cannot be left entirely to guesswork. Tools and platforms help in analyzing customer data and gauge buying patterns to make predictions of whether or not a customer will purchase a product or avail a service.

The salespeople have limited knowledge that is more or less based only on their expertise, traditional sales strategies, and their experience in the field. Because businesses today generate vast quantities of data sets, manually processing them is next to impossible.

How are different businesses using AI

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With AI, they can not only process big data in a short period but also use that data to extract actionable insights from it. 

4. AI can improve sales without adding increasing the headcount.

For any business owner, increasing the bottom line is the primary goal. And revenue and profit generation is directly related to sales. One way to boost sales is by hiring more talent.

That increases the overhead expenses of the business. Onboarding new employees, arranging a workstation and laptop for them, training them – everything costs money to the business – which at times won’t be viable.

The more effective solution to boost the sales function without hiring more personnel is by employing AI tools. The technology can help automate specific tasks such as forecasting, conducting follow-ups, lead scoring, and more, thereby freeing up the time of the sales teams to focus on core operations.

Businesses with accurate sales forecasts are 10% more likely to generate revenue! Why not make the most of it using artificial intelligence?

How to Predict Customer Churn Rate using AI in eCommerce

5. Using predictive analytics to improve sales pitches.

Predictive analytics, a subset of AI, has gained massive popularity across many areas in business. The primary goal of the PA systems is to predict specific outcomes of a situation in a given context and make related suggestions to the business.

33% of businesses lack in tracking customer journeys accurately. Because an AI system can track consumer behavior and analyze past buying data, it can predict with a certain level of accuracy whether or not a customer is likely to purchase the product.

This data set can also be used by salespeople to draft a customized pitch that is more engaging to a target customer base, thereby improving the rate of conversion and consequently increasing profits of the business.

6. AI can help explore all areas of opportunity.

The primary goal of any small business is to drive revenues with a minimum investment of resources. Perhaps one of the most significant advantages of using AI is its capability to process and analyze big data. AI systems are designed to process data to identify patterns and correlations.

These patterns may not be easily recognizable to humans. Artificial intelligence can identify them and accordingly provide suggestions as to how we can use them in business. For example, an AI system can suggest that sending weekly emails to subscribers will help improve open rates. Or it may indicate that the business customizes a product for a specific target audience.

Although these suggestions seem like minor nuances, they are beneficial to create better opportunities and enhance the growth of the business.

5 Ways Artificial Intelligence can Boost your Small Business

Summing it up

Everything matters when running a small business – time, resources, budget. Therefore, it is necessary to reduce the workload of ad-hoc tasks and instead focus on reaching maximum potential customers, converting them, and winning their loyalty for life.

Thankfully, Datoin, an automated AI-powered platform, helps improve the sales performance of small businesses. You can leverage AI for free, using Datoin. Sign up for a trial here – https://app.datoin.com/signup.

You can read about our services here.

5 Ways Artificial Intelligence can Boost your Small Business

Using artificial intelligence in your business increases your profitability and efficiency. Additionally, 85% of executives already believe that AI will help their businesses gain competitive advantage and sustain rapid developments.

It is no surprise that Artificial Intelligence (AI) has gained momentum across industries. From manufacturing and logistics to healthcare and retail – businesses from different sectors have started using AI-powered applications to improve their performance.

Many business owners dismiss implementing machine learning and AI as a daunting challenge. The biggest myth being, that AI is complicated and is understood by computer scientists or data engineers at bigger companies. In reality, numerous small businesses are leveraging AI. You shouldn’t wait, as your competitors certainly won’t.

With the rising implementation of AI, more and more companies are building AI applications, thereby driving down costs. The increased adoption has made AI accessible to a wide range of companies, in every business sector.

AI for SMB

A PwC study highlights that AI is expected to contribute $15.7 trillion to the global economy by 2030. That means there is a massive opportunity for businesses to leverage technology for their benefit.

Impact of artificial intelligence on the global GDP

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85% of executives already believe that AI will help their businesses gain competitive advantage and sustain rapid developments. It is vital for your small business to take advantage of this revolutionary technology. Here are the 5 ways in which you can do so, even on a tight budget.  

1. Efficient decision making

The past decade has witnessed a considerable improvement in storage and network technologies, thus bringing about the age of big data. However, the collected data is irrelevant if it can’t be analyzed.

It is humanly impossible to annotate and analyze large quantities of data manually. Fortunately, AI-based applications can take up the task. The analyzed data can enable small businesses to gain insights and arrive at better top-management decisions.

Let us give you an example: Walmart uses HANA, SAP’s data platform for data analytics. Given that the veteran retailer has 245 million customers globally, the amount of data generated on a daily basis is enormous.

HANA, built with machine learning algorithms, can quickly identify patterns in the data and enable Walmart employees to make better decisions.

As a small business owner, we know that you do not require such a customized platform nor have the budget for developing one. Alternately, you could use Datoin – an AI-based platform that helps you get actionable insights from your data.

You can implement AI for free, with Datoin to know the monthly churn, the customers likely to churn, the sales forecast on a plug-and-play model.

Click here to sign-up for using AI and Ml for free, with Datoin – https://app.datoin.com/signup.

2. Automated marketing and sales activities

Most AI applications are developed for automation workflow processes such as marketing, customer service, inventory management, and more to save time and boost productivity levels. As a business owner, you can integrate AI in your marketing strategy by introducing AI-powered chatbots to provide efficient customer service in real-time.

Then there are specific platforms such as Rapidminer also enable businesses to optimize and design sales campaigns by providing information on the competition, pricing strategies, consumer preferences, and more.

Another use case for AI in marketing is using tools such as Buffer and HootSuite to schedule social media posts or MailChimp for sending emails to customers at a particular time.

4 Tasks Worth Automating using Artificial Intelligence

3. Faster recruitment

Finding the right candidate for a job role is an arduous process involving many levels of the interview process and large amounts of paperwork. AI applications can help automate and streamline the recruitment process for your small business.

Impact of AI on recruitment

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Unilever, a multinational corporation manufacturing 400 products and employing 170,000 people, uses machine learning for efficiently hiring and processing approximately 1.8 million job applications on a yearly basis.

AI applications such as Hirevue enable candidates to give interviews on their smartphones by merely registering on the app. The audio and video data is then analyzed and shared with potential employers for the next steps in the recruitment process.

4. Robust data security and privacy

With cybercrime on the rise, one of the most important reasons for businesses to invest in the right AI solutions is to mitigate the risks of a security breach. Major tech companies such as Facebook and Google have come continuously under fire for lack of proper security measures for consumer data.

AI-based applications that are built for pattern recognition and anomaly detection help detect possible attempts of data theft and fraud. AI-solution provider Deepsense.ai, for example, uses machine learning algorithms to enable companies to build software that helps reduce the risk of fraud and adequately secure sensitive consumer data.

5. Efficient customer service

Perhaps, the most crucial innovation in customer service is that of chatbots. Consumers in today’s competitive market scenario look for quick responses to their problems without having to wait. A survey by Statista claims that 78% of companies use chatbots for self-service.

Chatbots mainly provide consumers a quick and effective platform to interact with businesses. Because chatbots can answer their queries within a span of a few seconds, they make the process far more effective, speedy, and efficient as compared to call center reps who may not always be able to provide answers in real-time.

4 Applications of Artificial Intelligence in eCommerce

Wrapping it up

So, for those who want to expand their businesses, AI is a must-have technology in today’s digital age. Carefully evaluate your business and identify the areas where this technology can be applied.

For instance, you can introduce chatbots on your website to increase customer engagement, or automate the process of inventory management, and so on. Before you adopt an AI solution into your workflow, you must calculate or estimate the ROI for the same.

If you want to hop on to the AI bandwagon, we have a solution: Datoin. We can help you kickstart your AI journey by identifying solution templates that are ideal for your business.

Intrigued?

Why don’t you use Datoin for free and see how it benefits your small business. You can sign up for a 1-month long FREE TRIAL here.

No obligations, no risk!

5 Pitfalls to Avoid when Implementing Machine Learning for your Small Business

Small businesses are rapidly implementing artificial intelligence to gain a competitive edge over competitors. Are they doing it right? Let’s talk about the common pitfalls to avoid while adopting machine learning for your SMB.

There has been a lot of excitement about the advancements in machine learning algorithms in the last few years. There are a number of problems that can be solved in sectors such as financial services, healthcare, retail and others.

According to BCG, 84% of businesses believe that investing in AI and ML leads to greater competitive advantages – whether it comes to expanding business offerings or making substantial process improvements.

5 Pitfalls to Avoid when Implementing Machine Learning for your Small Business

No wonder, small businesses are rapidly implementing artificial intelligence technologies to maximize their potential. While the benefits of deploying machine learning are numerous, ensure that you stay away from these 5 mistakes when introducing your business to AI or ML. 

1. Deploying unnecessarily complicated ML technologies

Given that machine learning is not widely adopted by small businesses, many SMB owners are not fully aware of the different ML technologies out there. They risk ending up with tools that need large volumes of data to understand even the most basic use cases of the technology.

In the language of ML, such a scenario is called overfitting. In other words, you can have the technology without sophisticated algorithms, but without good data, it will give a poor predictive performance.

you can have the technology without sophisticated algorithms, but without good data, it will give a poor predictive performance.

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Therefore, be sure to do your research and choose a machine learning tool that needs only a small quantity of data and can be set up to run in full production in just a few hours. A Data Dilemma Report states that 12.5% of staff time is lost during data collection. That’s five hours a week in a 40-hour workweek.

You can feed your existing data into Datoin, an automated AI-platform. Using machine learning, it helps you predict the customer churn rate, the customers likely to churn, the daily sales and the demand for each product in your inventory.  This way, you save valuable time and resources and start gaining much faster returns on the investment you made on the ML technology.

To start leveraging machine learning for free, for your business, sign up for a trial here – https://app.datoin.com/signup.

2. Assuming where to use ML technology

When it comes to organizational process knowledge, most businesses – big and small – are compartmentalized. The top management team is usually not involved in the day-to-day processes, and neither do they have access to process documentation.

As a result, the processes that you start applying machine learning to are not necessarily the most appropriate processes to work with. Business execs are using artificial intelligence to automate repetitive tasks such as timesheets (78%), scheduling (79%), and paperwork (82%).

Business execs are using the technology to automate repetitive tasks such as timesheets (78%), scheduling (79%), and paperwork (82%).
Artificia; intelligence in decision making

It is thus crucial to incorporate process intelligence to determine which areas of work are genuinely ready for automation before you go ahead with a project.

A comprehensive understanding – based on facts, not opinion – of where machine learning will work and the kind of value-add and savings these technologies will bring to your business is critical.

3. Forgetting that it is a continuous process

Merely planning out your machine learning activities, deploying digital workers, and training your business algorithms is not enough. It is imperative to monitor every step of the process post-implementation and to assess your digital workforce regularly.

Machine learning is not a self-sufficient process. It calls for continuous measurement of the impact of automation at each stage to:

  • Ensure protocol compliance at each stage
  • Prevent bottlenecks from arising
  • Ensure that automation is not causing any adverse effects at any point along the way

4. Missing out on high-value business cases

Most businesses tend to go for conventional options that center on what has worked before. They are thus likely to apply the technology to the task that recurs most frequently because such a task has the appearance of giving reliable results.

However, this kind of ad hoc approach to process choosing is likely to end up leaving out other business opportunities that might recur less often but which have high ROI. As a business, you should have a clear plan in mind of how you want to “land and expand” with machine learning throughout your company.

What are your organisation's priorities in 2020?

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While it is understandable that you would want to start with processes that involve minimal disruption to the business or the way you interact with end-users, your ultimate organizational goals should be automating tasks to bring in the maximum ROI.

5. Relying too much on Robotic Process Automation (RPA)

RPA is easy to deploy, and its digital workers can be configured without trouble and can work just like humans once they are in place. Besides, it can considerably boost your company’s efficiencies by connecting with external data sources and legacy systems.

It is crucial to remember that RPA is focused on structured, repetitive work. On the other hand, machine learning can be applied to both structured and unstructured work.

When you add machine learning technology to RPA, the digital workers gain the cognitive skills necessary to extract useful information from different types of content, understand the intent behind and meaning of different kinds of documents, and enhance their decision-making capabilities. Your business should thus avoid relying on RPA alone.

Over to you

Machine learning has immense potential, if used correctly. This includes boosting sales, attracting more customers, forecasting demand and ultimately driving profits.  

Luckily, Datoin, an ML-driven AI platform can help you experiment with data, for free, to know how you can use AI and ML for your small business.  

Sign up for a trial here, and see how the platform can add value to your business, for free.

6 Applications of Artificial Intelligence for Small Businesses on a Budget

AI-boosted service is no longer limited to big technology companies and the corporates. Thanks to Datoin, a new generation AI-based automation platform, AI can be utilized for targeting and selling to new customers by companies of all sizes.

Continue reading “6 Applications of Artificial Intelligence for Small Businesses on a Budget”

5 Ways eCommerce Brands Can Use Artificial Intelligence for Black Friday

Black Friday is a treasure trove for e-retailers who see it as the perfect opportunity to attract more customers and drive higher sales. Here’s how your eCommerce brand can use artificial intelligence (AI) to get the most out of the Black Friday:

Continue reading “5 Ways eCommerce Brands Can Use Artificial Intelligence for Black Friday”