Who is it? by Bizcam is a mobile CRM & Clienteling application built on the Salesforce Platoform that leverages the latest in Facial Detection & Recognition technology to give brick and mortar retailers the ability to better know their customers.
SaaS – Web-based software with no servers to buy, install, or maintain. Receive software updates automatically and never have to worry about infrastructure, uptime, or scalability.
Device Agnostic – Access the software from any device with an internet connection. Use any web browser on Windows and Mac devices, as well as native apps for iOS and Android devices.
Mobile Optimized – With native apps for iOS and Android mobile and tablet devices, the entire user experience is optimized to give salespeople the information they need right at their finger tips while on the sales floor.
POS Integration – View customer’s sales transaction data right within the mobile application with built-in support for integration to your point-of- sale system.
Salesforce Platform – Built on the world’s #1 CRM platform, giving you all the tools you need to know your customers.
As customers enter your store, provide your salespeople with the information they need in real-time on their mobile & tablet devices to:
Proactively identify & greet customers
View the customer’s profile & account information
View the customer’s past purchase history
Offer targeted product suggestions
Modify & personalize the shopping experience
Once the business day is over, give you and your staff the information you need to make smarter data-driven decisions with the same metrics used by online retailers:
Evaluate store performance by tracking conversion ratios, total visits, repeat visits, bounce ratios, and much more
Tie visits to marketing campaigns and evaluate marketing efficacy
Micro-segment your customers and perform personalized and targeted marketing
Gain a better understanding of your customer demographics how they change throughout the day
Allow all of your salespeople to access a single source of information about all of your customers and proactively identify customers even they’ve never assisted them before.
Example: Jane buys a new television from salesperson Mary at an electronics store. After she gets home, Jane realizes that the television does not fit properly in her living room and returns the next day to exchange it. Mary is not working that day, but salesperson Martha is alerted when Jane enters the store and is able see Jane’s transaction from the previous day and she proactively asks Jane if everything is OK with her recent purchase, despite never having assisted Jane in the past.
Allow all of your store locations to access a single source of information about all of your customers and proactively identify customers even if it’s their first time visiting a ocation.
Example: Steve is a frequent customer of your watch store in Boston. He is on vacation where he enters your Las Vegas location. The salesperson is able to proactively identify Steve as a high-value customer, despite it being his first visit to the Las Vegas location. By viewing his purchase history from Boston, the salesperson can offer suggestions about a new watch in the same collection that Steve has purchased from in the past.
Create a streamlined and personalized experience for your customers across all of your channels, both online and offline, and maintain a 360° view of all customers at all times.
Example: Liz buys a pair of shoes online. After receiving them in the mail, she realizes that they do not fit properly. She calls in to the call center where the agent informs her that there is a store location 5 miles from her home that has the shoes in the right size in stock and that she can exchange the shoes at her convenience by visiting the store. When Liz enters the store, the salesperson is able to identify her and immediately view her online transaction and process the return.
Leverage the analytical data stored in the system to uncover additional sales opportunities that may have otherwise have gone unnoticed.
Example: Stephanie visits her favorite jewelry store and looks at a necklace with salesperson Julie. Stephanie decides not to purchase the necklace and leaves the store. A few weeks later that particular necklace is put on sale by the store as part of a holiday promotion. Julie looks back in the system and sees that Stephanie visited the store and looked at that necklace but did not purchase it. Julie gives Stephanie a call and follows up with an email to let her know about the sale. Stephanie returns to the store a few days later, Julie is proactively alerted once she walks in and greets Stephanie, and she decides to purchase the necklace.
Gain a better understanding of the response to your marketing efforts and make smarter decisions about where to spend precious marketing dollars.
Example: Derrick, the owner of a men’s clothing boutique, sends out two email campaigns: one to his current customers and one to potential new customers. After tracking the number of current vs. new customers that came into his store in the following weeks, he sees that email is much more effective at getting current customers to return than attracting new customers. He decides to increase his email campaign to current customers, while testing taking out an ad in his local newspaper to attract new customers.